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On the Performance Overhead of BPMN Modeling Practices

Ana Ivanchikj, profile picture
Ana Ivanchikj

The document discusses the impacts of different BPMN modeling practices on the performance of business process instances. It outlines research questions focusing on execution duration and ranking of performance among semantically equivalent but structurally different models. The methodology includes designing initial models, applying transformation rules, measuring performance, and analyzing results.

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On  the   Performance  Overhead  of BPMN  Modeling  Practices   Ana  Ivanchikj Vincenzo  Ferme Cesare  Pautasso University  of  Lugano  (USI) Switzerland
2 BPMN  Expressiveness
3 BPMN  Expressiveness BPMN  Standard
4 BPMN  Expressiveness BPMN  Standard Model’s  Semantics
5 BPMN  Expressiveness BPMN  Standard Model’s  Semantics Model’s  Understandability
6 B A C B A C
7 Structural  Differences B A C B A C
8 Structural  Differences B A C B A C Semantical  Equivalence
9 Structural  Differences B A C B A C Semantical  Equivalence case  id trace 1 ABC 2 ACB 3 ABC …. ….
10 Structural  Differences B A C B A C Semantical  Equivalence case  id trace 1 ABC 2 ACB 3 ABC …. …. Performance  Equivalence
11 Structural  Differences B A C B A C Semantical  Equivalence case  id trace 1 ABC 2 ACB 3 ABC …. …. Performance  Equivalence
12 Research  Questions RQ1: Does  the  application  of  different  modeling  practices  have  a   significant  impact  on  the  duration  of  a  BP  instance  execution?  
13 Research  Questions RQ1: Does  the  application  of  different  modeling  practices  have  a   significant  impact  on  the  duration  of  a  BP  instance  execution?  
14 Research  Questions RQ1: Does  the  application  of  different  modeling  practices  have  a   significant  impact  on  the  duration  of  a  BP  instance  execution?  
15 Research  Questions RQ1: Does  the  application  of  different  modeling  practices  have  a   significant  impact  on  the  duration  of  a  BP  instance  execution?  
16 Research  Questions RQ1: Does  the  application  of  different  modeling  practices  have  a   significant  impact  on  the  duration  of  a  BP  instance  execution?   RQ2: Is  there  a  total  order  between  semantically  equivalent  but   structurally  different  models,  when  ranked  according  to  their   performance?  
RQ2: Is  there  a  total  order  between  semantically  equivalent  but   structurally  different  models,  when  ranked  according  to  their   performance?   17 Research  Questions RQ1: Does  the  application  of  different  modeling  practices  have  a   significant  impact  on  the  duration  of  a  BP  instance  execution?  
18 Methodology
19 Methodology 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) 4. Execute the BPs in EM and Measure Performance 2. Determine Applicable Transformation Rules Transformation rules (R) Applicable combinations of rules (RA) Load function / WfMS Semantically equivalent BP models (TMi) 3. Generate Transformed BP Models i <= z i>z Unsaved diagram Performance metrics 5. Test Statistical Significance of Differences 6. Rank the Performance of Transformed Models Statistical significance of the performance differences RQ1 RQ2
20 Methodology 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) 4. Execute the BPs in EM and Measure Performance 2. Determine Applicable Transformation Rules Transformation rules (R) Applicable combinations of rules (RA) Load function / WfMS Semantically equivalent BP models (TMi) 3. Generate Transformed BP Models i <= z i>z Unsaved diagram Performance metrics 5. Test Statistical Significance of Differences 6. Rank the Performance of Transformed Models Statistical significance of the performance differences RQ1 RQ2 Experiment  definition  and  execution
21 Methodologym 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) 4. Execute the BPs in EM and Measure Performance 2. Determine Applicable Transformation Rules Transformation rules (R) Applicable combinations of rules (RA) Load function / WfMS Semantically equivalent BP models (TMi) 3. Generate Transformed BP Models i <= z i>z Experiment  definition  and  execution
22 Methodology 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) 4. Execute the BPs in EM and Measure Performance 2. Determine Applicable Transformation Rules Transformation rules (R) Applicable combinations of rules (RA) Load function / WfMS Semantically equivalent BP models (TMi) 3. Generate Transformed BP Models i <= z i>z Unsaved diagram Performance metrics 5. Test Statistical Significance of Differences 6. Rank the Performance of Transformed Models Statistical significance of the performance differences RQ1 RQ2 Experiment  definition  and  execution
23 Methodology 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) 4. Execute the BPs in EM and Measure Performance 2. Determine Applicable Transformation Rules Transformation rules (R) Applicable combinations of rules (RA) Load function / WfMS Semantically equivalent BP models (TMi) 3. Generate Transformed BP Models i <= z i>z Unsaved diagram Performance metrics 5. Test Statistical Significance of Differences 6. Rank the Performance of Transformed Models Statistical significance of the performance differences RQ1 RQ2 Experiment  definition  and  execution Results  analysis  and  ranking
24 Methodology Results  analysis  and  ranking Performance metrics 5. Test Statistical Significance of Differences 6. Rank the Performance of Transformed Models Statistical significance of the performance differences RQ1 RQ2
25 Methodology 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) 4. Execute the BPs in EM and Measure Performance 2. Determine Applicable Transformation Rules Transformation rules (R) Applicable combinations of rules (RA) Load function / WfMS Semantically equivalent BP models (TMi) 3. Generate Transformed BP Models i <= z i>z Unsaved diagram Performance metrics 5. Test Statistical Significance of Differences 6. Rank the Performance of Transformed Models Statistical significance of the performance differences RQ1 RQ2 Experiment  definition  and  execution Results  analysis  and  ranking
26 First models v4 EX1_PCF EX2_E 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2 Empty ST 2 EG 2.1 Empty ST 2 Empty ST 2 EG 2.2 EG 2.4 EG EG Generate ST 2.1 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi)
27 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) First models v4 EX1_PCF EX2_E 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2 Empty ST 2 EG 2.1 Empty ST 2 Empty ST 2 EG 2.2 EG 2.4 EG EG Generate ST 2.1 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 minimize  the  routing   paths  per  element match  every  split  with  a   join  of  the  same  type   1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) use  one  start  and   one  end  event  
28 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) First models v4 EX1_PCF EX2_E 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2 Empty ST 2 EG 2.1 Empty ST 2 Empty ST 2 EG 2.2 EG 2.4 EG EG Generate ST 2.1 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 minimize  the  routing   paths  per  element match  every  split  with  a   join  of  the  same  type   1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) use  one  start  and   one  end  event   1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi)
29 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) First models v4 EX1_PCF EX2_E 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2 Empty ST 2 EG 2.1 Empty ST 2 Empty ST 2 EG 2.2 EG 2.4 EG EG Generate ST 2.1 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 minimize  the  routing   paths  per  element match  every  split  with  a   join  of  the  same  type   1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) use  one  start  and   one  end  event   Parallel
30 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) First models v4 EX1_PCF EX2_E 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2 Empty ST 2 EG 2.1 Empty ST 2 Empty ST 2 EG 2.2 EG 2.4 EG EG Generate ST 2.1 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 First models v4 EX1_PCF EX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 3 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 minimize  the  routing   paths  per  element match  every  split  with  a   join  of  the  same  type   1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) use  one  start  and   one  end  event   Parallel Exclusive
31 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) First models v4 EX1_PCF EX2_E 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2 Empty ST 2 EG 2.1 Empty ST 2 Empty ST 2 EG 2.2 EG 2.4 EG EG Generate ST 2.1 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 First models v4 EX1_PCF EX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 3 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 minimize  the  routing   paths  per  element match  every  split  with  a   join  of  the  same  type   1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) use  one  start  and   one  end  event   avoid  OR   gateways   Parallel Exclusive Inclusive
2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) r2    Coalesce  Splitsr1 Coalesce  Joins r3    Use  Inclusive  Gateway r4 Use  Implicit  Gateway 32
2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) r2    Coalesce  Splitsr1 Coalesce  Joins r3    Use  Inclusive  Gateway r4 Use  Implicit  Gateway 33 Semantics Preserving Transformation Rules!
34 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) r1 Coalesce  Joins
r2    Coalesce  Splits 35 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA)
r3    Use  Inclusive  Gateway 36 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA)
r4 Use  Implicit  Gateway 37 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA)
2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) r2    Coalesce  Splitsr1 Coalesce  Joins r3    Use  Inclusive  Gateway r4 Use  Implicit  Gateway 38 Semantics Preserving Transformation Rules!
2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) r2    Coalesce  Splitsr1 Coalesce  Joins r3    Use  Inclusive  Gateway r4 Use  Implicit  Gateway 39 Semantics Preserving Transformation Rules! 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA)
1.1.Parallel_Multiple 1.1 Start Empty ST 1.1.1 PG 1.1.1 PG 1.1.2 PG 1.1.4 Empty ST 1.1.2 Empty ST 1.1.3 Empty ST 1.1.4 Empty ST 1.1.5 PG 1.1.3 PG 1.1.5 PG 1.1.6 1.1 End Initial   Model 40
1.1.Parallel_Multiple 1.1 Start Empty ST 1.1.1 PG 1.1.1 PG 1.1.2 PG 1.1.4 Empty ST 1.1.2 Empty ST 1.1.3 Empty ST 1.1.4 Empty ST 1.1.5 PG 1.1.3 PG 1.1.5 PG 1.1.6 1.1 End Initial   Model 41 coalesce   joinst1 t2 t3 use   inclusive   gateway use   implicit gateway t4 coalesce   splits 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA)
1.1.Parallel_Multiple 1.1 Start Empty ST 1.1.1 PG 1.1.1 PG 1.1.2 PG 1.1.4 Empty ST 1.1.2 Empty ST 1.1.3 Empty ST 1.1.4 Empty ST 1.1.5 PG 1.1.3 PG 1.1.5 PG 1.1.6 1.1 End Initial   Model 42 coalesce   joinst1 t2 t3 use   inclusive   gateway use   implicit gateway t4 coalesce   splits 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA)
tiple 1.1 Start Empty ST 1.1.1 PG 1.1.1 PG 1.1.2 PG 1.1.4 Empty ST 1.1.2 Empty ST 1.1.3 Empty ST 1.1.4 Empty ST 1.1.5 PG 1.1.3 PG 1.1.5 PG 1.1.6 1.1 End Initial   Model 43 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) R1_Parallel_Coalesce_Joins R1.PG Start Empty ST R1.PG.1 PG R1.PG.1 PG R1.PG.2 PG R1.PG.3 Empty ST R1.PG.2 Empty ST R1.PG.3 Empty ST R1.PG.4 Empty ST R1.PG.5 PG R1.PG.4 R1.PG End t1 coalesce   joins
44 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) R2_Parallel_Coalesce_Splits R2.PG Start Empty ST R2.PG.1 PG R2.PG.1 Empty ST R2.PG.2 Empty ST R2.PG.3 Empty ST R2.PG.4 Empty ST R2.PG.5 PG R2.PG.2 PG R2.PG.3 PG 1.1.6 R2.PG End tiple 1.1 Start Empty ST 1.1.1 PG 1.1.1 PG 1.1.2 PG 1.1.4 Empty ST 1.1.2 Empty ST 1.1.3 Empty ST 1.1.4 Empty ST 1.1.5 PG 1.1.3 PG 1.1.5 PG 1.1.6 1.1 End Initial   Model t2 coalesce   splits
45 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) R3_Parallel_Alternative R3.PG Start Empty ST R3.PG.1 Empty ST R3.PG.2 Empty ST R3.PG.3 Empty ST R3.PG.4 Empty ST R3.PG.5 R3.PG EndIG R3.PG.1 IG R3.PG.2 IG R3.PG.4 IG R3.PG.3 IG R3.PG.5 IG R3.PG.6 tiple 1.1 Start Empty ST 1.1.1 PG 1.1.1 PG 1.1.2 PG 1.1.4 Empty ST 1.1.2 Empty ST 1.1.3 Empty ST 1.1.4 Empty ST 1.1.5 PG 1.1.3 PG 1.1.5 PG 1.1.6 1.1 End Initial   Model t3 use   inclusive   gateway
46 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) tiple 1.1 Start Empty ST 1.1.1 PG 1.1.1 PG 1.1.2 PG 1.1.4 Empty ST 1.1.2 Empty ST 1.1.3 Empty ST 1.1.4 Empty ST 1.1.5 PG 1.1.3 PG 1.1.5 PG 1.1.6 1.1 End Initial   Model t4 use   implicit gateway R4_Parallel_Activity_Form R4.PG Start Empty ST R4.PG.1 PG R4.PG.1 PG R4.PG.3 Empty ST R4.PG.2 Empty ST R4.PG.3 Empty ST R4.PG.4 Empty ST R4.PG.5 PG R4.PG.2 PG R4.PG.4 PG R4.PG.5 R4.PG End
use   implicit gateway t3 use   inclusive   gateway coalesce   joins 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) t4 1.1.Parallel_Multiple 1.1 Start Empty ST 1.1.1 PG 1.1.1 PG 1.1.2 PG 1.1.4 Empty ST 1.1.2 Empty ST 1.1.3 Empty ST 1.1.4 Empty ST 1.1.5 PG 1.1.3 PG 1.1.5 PG 1.1.6 1.1 End R1_Parallel_Coalesce_Joins R1.PG Start Empty ST R1.PG.1 PG R1.PG.1 PG R1.PG.2 PG R1.PG.3 Empty ST R1.PG.2 Empty ST R1.PG.3 Empty ST R1.PG.4 Empty ST R1.PG.5 PG R1.PG.4 R1.PG End t1 Initial   Model R2_Parallel_Coalesce_Splits R2.PG Start Empty ST R2.PG.1 PG R2.PG.1 Empty ST R2.PG.2 Empty ST R2.PG.3 Empty ST R2.PG.4 Empty ST R2.PG.5 PG R2.PG.2 PG R2.PG.3 PG 1.1.6 R2.PG End t2 coalesce   splits R3_Parallel_Alternative R3.PG Start Empty ST R3.PG.1 Empty ST R3.PG.2 Empty ST R3.PG.3 Empty ST R3.PG.4 Empty ST R3.PG.5 R3.PG EndIG R3.PG.1 IG R3.PG.2 IG R3.PG.4 IG R3.PG.3 IG R3.PG.5 IG R3.PG.6 ctivity_Form R4.PG Start Empty ST R4.PG.1 PG R4.PG.1 PG R4.PG.3 Empty ST R4.PG.2 Empty ST R4.PG.3 Empty ST R4.PG.4 Empty ST R4.PG.5 PG R4.PG.2 PG R4.PG.4 PG R4.PG.5 R4.PG End 47
use   implicit gateway t3 use   inclusive   gateway 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) t4 1.1.Parallel_Multiple 1.1 Start Empty ST 1.1.1 PG 1.1.1 PG 1.1.2 PG 1.1.4 Empty ST 1.1.2 Empty ST 1.1.3 Empty ST 1.1.4 Empty ST 1.1.5 PG 1.1.3 PG 1.1.5 PG 1.1.6 1.1 End R1_Parallel_Coalesce_Joins R1.PG Start Empty ST R1.PG.1 PG R1.PG.1 PG R1.PG.2 PG R1.PG.3 Empty ST R1.PG.2 Empty ST R1.PG.3 Empty ST R1.PG.4 Empty ST R1.PG.5 PG R1.PG.4 R1.PG End t1 Initial   Model R2_Parallel_Coalesce_Splits R2.PG Start Empty ST R2.PG.1 PG R2.PG.1 Empty ST R2.PG.2 Empty ST R2.PG.3 Empty ST R2.PG.4 Empty ST R2.PG.5 PG R2.PG.2 PG R2.PG.3 PG 1.1.6 R2.PG End t2 coalesce   splits R3_Parallel_Alternative R3.PG Start Empty ST R3.PG.1 Empty ST R3.PG.2 Empty ST R3.PG.3 Empty ST R3.PG.4 Empty ST R3.PG.5 R3.PG EndIG R3.PG.1 IG R3.PG.2 IG R3.PG.4 IG R3.PG.3 IG R3.PG.5 IG R3.PG.6 ctivity_Form R4.PG Start Empty ST R4.PG.1 PG R4.PG.1 PG R4.PG.3 Empty ST R4.PG.2 Empty ST R4.PG.3 Empty ST R4.PG.4 Empty ST R4.PG.5 PG R4.PG.2 PG R4.PG.4 PG R4.PG.5 R4.PG End 48 coalesce   joins
use   implicit gateway t3 use   inclusive   gateway t4 1.1.Parallel_Multiple 1.1 Start Empty ST 1.1.1 PG 1.1.1 PG 1.1.2 PG 1.1.4 Empty ST 1.1.2 Empty ST 1.1.3 Empty ST 1.1.4 Empty ST 1.1.5 PG 1.1.3 PG 1.1.5 PG 1.1.6 1.1 End R1_Parallel_Coalesce_Joins R1.PG Start Empty ST R1.PG.1 PG R1.PG.1 PG R1.PG.2 PG R1.PG.3 Empty ST R1.PG.2 Empty ST R1.PG.3 Empty ST R1.PG.4 Empty ST R1.PG.5 PG R1.PG.4 R1.PG End t1 Initial   Model R2_Parallel_Coalesce_Splits R2.PG Start Empty ST R2.PG.1 PG R2.PG.1 Empty ST R2.PG.2 Empty ST R2.PG.3 Empty ST R2.PG.4 Empty ST R2.PG.5 PG R2.PG.2 PG R2.PG.3 PG 1.1.6 R2.PG End t2 coalesce   splits R3_Parallel_Alternative R3.PG Start Empty ST R3.PG.1 Empty ST R3.PG.2 Empty ST R3.PG.3 Empty ST R3.PG.4 Empty ST R3.PG.5 R3.PG EndIG R3.PG.1 IG R3.PG.2 IG R3.PG.4 IG R3.PG.3 IG R3.PG.5 IG R3.PG.6 ctivity_Form R4.PG Start Empty ST R4.PG.1 PG R4.PG.1 PG R4.PG.3 Empty ST R4.PG.2 Empty ST R4.PG.3 Empty ST R4.PG.4 Empty ST R4.PG.5 PG R4.PG.2 PG R4.PG.4 PG R4.PG.5 R4.PG End 49 coalesce   joins 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA)
R3R4 1.2.8 Start Empty ST 1.2.8.1 Empty ST 1.2.8.2 Empty ST 1.2.8.3 Empty ST 1.2.8.4 Empty ST 1.2.8.5 1.2.8 End IG 1.2.8.2 IG 1.2.8.4 IG 1.2.8.5 IG 1.2.8.1 IG 1.2.8.3 use   implicit gateway t3 use   inclusive   gateway 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) t4 1.1.Parallel_Multiple 1.1 Start Empty ST 1.1.1 PG 1.1.1 PG 1.1.2 PG 1.1.4 Empty ST 1.1.2 Empty ST 1.1.3 Empty ST 1.1.4 Empty ST 1.1.5 PG 1.1.3 PG 1.1.5 PG 1.1.6 1.1 End R1_Parallel_Coalesce_Joins R1.PG Start Empty ST R1.PG.1 PG R1.PG.1 PG R1.PG.2 PG R1.PG.3 Empty ST R1.PG.2 Empty ST R1.PG.3 Empty ST R1.PG.4 Empty ST R1.PG.5 PG R1.PG.4 R1.PG End t1 Initial   Model R2_Parallel_Coalesce_Splits R2.PG Start Empty ST R2.PG.1 PG R2.PG.1 Empty ST R2.PG.2 Empty ST R2.PG.3 Empty ST R2.PG.4 Empty ST R2.PG.5 PG R2.PG.2 PG R2.PG.3 PG 1.1.6 R2.PG End t2 coalesce   splits R3_Parallel_Alternative R3.PG Start Empty ST R3.PG.1 Empty ST R3.PG.2 Empty ST R3.PG.3 Empty ST R3.PG.4 Empty ST R3.PG.5 R3.PG EndIG R3.PG.1 IG R3.PG.2 IG R3.PG.4 IG R3.PG.3 IG R3.PG.5 IG R3.PG.6 ctivity_Form R4.PG Start Empty ST R4.PG.1 PG R4.PG.1 PG R4.PG.3 Empty ST R4.PG.2 Empty ST R4.PG.3 Empty ST R4.PG.4 Empty ST R4.PG.5 PG R4.PG.2 PG R4.PG.4 PG R4.PG.5 R4.PG End 1.2.1 Parallel_R1R2 1.2.1 Start Empty ST 1.2.1.1 PG 1.2.1.1 Empty ST 1.2.1.2 Empty ST 1.2.1.5 Empty ST 1.2.1.4 Empty ST 1.2.1.3 PG 1.2.1.2 1.2.1 End R4 1.2.3 Start Empty ST 1.2.3.1 PG 1.2.3.1 PG 1.2.3.2 Empty ST 1.2.3.2 Empty ST 1.2.3.3 Empty ST 1.2.3.4 Empty ST 1.2.3.5 PG 1.2.3.3 1.2.3 End 1.2.5 Parallel_R2R3 1.2.5 Start Empty ST 1.2.5.1 Empty ST 1.2.5.2 Empty ST 1.2.5.3 Empty ST 1.2.5.4 Empty ST 1.2.5.5 1.2.5 EndIG 1.2.5.1 IG 1.2.5.2 IG 1.2.5.3 IG 1.2.5.4 50 3. Generate Transformed BP Models Applicable combinations of rules (RA) Semantically equivalent BP models (TMi) coalesce   joins
R3R4 1.2.8 Start Empty ST 1.2.8.1 Empty ST 1.2.8.2 Empty ST 1.2.8.3 Empty ST 1.2.8.4 Empty ST 1.2.8.5 1.2.8 End IG 1.2.8.2 IG 1.2.8.4 IG 1.2.8.5 IG 1.2.8.1 IG 1.2.8.3 use   implicit gateway t3 use   inclusive   gateway 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) t4 1.1.Parallel_Multiple 1.1 Start Empty ST 1.1.1 PG 1.1.1 PG 1.1.2 PG 1.1.4 Empty ST 1.1.2 Empty ST 1.1.3 Empty ST 1.1.4 Empty ST 1.1.5 PG 1.1.3 PG 1.1.5 PG 1.1.6 1.1 End R1_Parallel_Coalesce_Joins R1.PG Start Empty ST R1.PG.1 PG R1.PG.1 PG R1.PG.2 PG R1.PG.3 Empty ST R1.PG.2 Empty ST R1.PG.3 Empty ST R1.PG.4 Empty ST R1.PG.5 PG R1.PG.4 R1.PG End t1 Initial   Model R2_Parallel_Coalesce_Splits R2.PG Start Empty ST R2.PG.1 PG R2.PG.1 Empty ST R2.PG.2 Empty ST R2.PG.3 Empty ST R2.PG.4 Empty ST R2.PG.5 PG R2.PG.2 PG R2.PG.3 PG 1.1.6 R2.PG End t2 coalesce   splits R3_Parallel_Alternative R3.PG Start Empty ST R3.PG.1 Empty ST R3.PG.2 Empty ST R3.PG.3 Empty ST R3.PG.4 Empty ST R3.PG.5 R3.PG EndIG R3.PG.1 IG R3.PG.2 IG R3.PG.4 IG R3.PG.3 IG R3.PG.5 IG R3.PG.6 ctivity_Form R4.PG Start Empty ST R4.PG.1 PG R4.PG.1 PG R4.PG.3 Empty ST R4.PG.2 Empty ST R4.PG.3 Empty ST R4.PG.4 Empty ST R4.PG.5 PG R4.PG.2 PG R4.PG.4 PG R4.PG.5 R4.PG End 1.2.1 Parallel_R1R2 1.2.1 Start Empty ST 1.2.1.1 PG 1.2.1.1 Empty ST 1.2.1.2 Empty ST 1.2.1.5 Empty ST 1.2.1.4 Empty ST 1.2.1.3 PG 1.2.1.2 1.2.1 End R4 1.2.3 Start Empty ST 1.2.3.1 PG 1.2.3.1 PG 1.2.3.2 Empty ST 1.2.3.2 Empty ST 1.2.3.3 Empty ST 1.2.3.4 Empty ST 1.2.3.5 PG 1.2.3.3 1.2.3 End 1.2.5 Parallel_R2R3 1.2.5 Start Empty ST 1.2.5.1 Empty ST 1.2.5.2 Empty ST 1.2.5.3 Empty ST 1.2.5.4 Empty ST 1.2.5.5 1.2.5 EndIG 1.2.5.1 IG 1.2.5.2 IG 1.2.5.3 IG 1.2.5.4 mi t1 t2 t3 t4 t12 t13 t14 t23 t24 t34 t123 t124 t134 t234 t1234 51 3. Generate Transformed BP Models Applicable combinations of rules (RA) Semantically equivalent BP models (TMi) 3. Generate Transformed BP Models Applicable combinations of rules (RA) Semantically equivalent BP models (TMi) coalesce   joins
52 First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 1.2.1 Parallel_R1R2 1.2.1 Start Empty ST 1.2.1.1 PG 1.2.1.1 Empty ST 1.2.1.2 Empty ST 1.2.1.5 Empty ST 1.2.1.4 Empty ST 1.2.1.3 PG 1.2.1.2 1.2.1 End First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 Workload benchflow [ICPE  ’16][BPM  ’15]
53 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 1.2.1 Parallel_R1R2 1.2.1 Start Empty ST 1.2.1.1 PG 1.2.1.1 Empty ST 1.2.1.2 Empty ST 1.2.1.5 Empty ST 1.2.1.4 Empty ST 1.2.1.3 PG 1.2.1.2 1.2.1 End First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 Workload benchflow [ICPE  ’16][BPM  ’15]
54 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics WfMS First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 1.2.1 Parallel_R1R2 1.2.1 Start Empty ST 1.2.1.1 PG 1.2.1.1 Empty ST 1.2.1.2 Empty ST 1.2.1.5 Empty ST 1.2.1.4 Empty ST 1.2.1.3 PG 1.2.1.2 1.2.1 End First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 Workload Load  function benchflow [ICPE  ’16][BPM  ’15]
55 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics WfMS First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 1.2.1 Parallel_R1R2 1.2.1 Start Empty ST 1.2.1.1 PG 1.2.1.1 Empty ST 1.2.1.2 Empty ST 1.2.1.5 Empty ST 1.2.1.4 Empty ST 1.2.1.3 PG 1.2.1.2 1.2.1 End First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 Workload Load  function benchflow [ICPE  ’16][BPM  ’15]
56 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics WfMS First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 1.2.1 Parallel_R1R2 1.2.1 Start Empty ST 1.2.1.1 PG 1.2.1.1 Empty ST 1.2.1.2 Empty ST 1.2.1.5 Empty ST 1.2.1.4 Empty ST 1.2.1.3 PG 1.2.1.2 1.2.1 End First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 Workload Load  function benchflow [ICPE  ’16][BPM  ’15]
57 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics WfMS First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 1.2.1 Parallel_R1R2 1.2.1 Start Empty ST 1.2.1.1 PG 1.2.1.1 Empty ST 1.2.1.2 Empty ST 1.2.1.5 Empty ST 1.2.1.4 Empty ST 1.2.1.3 PG 1.2.1.2 1.2.1 End First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 Workload Load  function Metrics benchflow [ICPE  ’16][BPM  ’15]
58 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics WfMS First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 1.2.1 Parallel_R1R2 1.2.1 Start Empty ST 1.2.1.1 PG 1.2.1.1 Empty ST 1.2.1.2 Empty ST 1.2.1.5 Empty ST 1.2.1.4 Empty ST 1.2.1.3 PG 1.2.1.2 1.2.1 End First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 Workload Load  function Metrics benchflow [ICPE  ’16][BPM  ’15] instance  duration  in   milliseconds  (ms)  
59 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics 0 100 200 300 400 500 Users Time  (min:sec) 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics v 7.5
60 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics Vincenzo  Ferme 0 100 200 300 400 500 Users Time  (min:sec) 0 10 20 30 40 50 Users Time  (min:sec) 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics v 7.5 v 5.21
61 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics 1 second think time Vincenzo  Ferme 0 100 200 300 400 500 Users Time  (min:sec) 0 10 20 30 40 50 Users Time  (min:sec) 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics v 7.5 v 5.21
Results  discussion
63 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics Instance  duration (ms) Parallel mi t124 2.59  ms ± 0.05  ms 2.16  ms ± 0.03  ms Exclusive t3 t124 1.57  ms ± 0.02  ms 1.32  ms ± 0.02  ms Inclusive mi t1234 2.76  ms ± 0.08  ms 1.78  ms ± 0.02  ms Parallel mi t23 26.04  ms ± 0.01  ms 15.62  ms ± 0.12  ms Exclusive mi t124 2.14  ms ± 0.07  ms 1.39  ms ± 0.02  ms Inclusive mi t1234 29.87  ms ± 0.30  ms 9.93  ms ± 0.14  ms
64 5. Test Statistical Significance of Differences Performance metrics Statistical significance of the performance differences *http://www.biochemia-­‐medica.com/content/comparing-­‐groups-­‐statistical-­‐differences-­‐how-­‐choose-­‐right-­‐statistical-­‐test Population One  sample Two  samples Three  or  more   samples Drawn  from   a  normal   distribution? Drawn  from   a  normal   distribution? Drawn  from   a  normal   distribution? One sample t-­‐test Wilcoxon rank  sum test Paired   samples? Equal variance? Paired t-­‐test Unaired t-­‐test Welch’s corrected unpaired  test Wilcoxon’s matched pairs  test Mann-­‐Whitney test Paired   samples? Paired   samples? Repeated measures one-­‐way  ANOVA Paired   samples? One-­‐way   ANOVA Friedman test Kruskal-­‐Wallis test Yes Yes Yes Yes Yes Yes Yes Yes No No No No No No No No
65 5. Test Statistical Significance of Differences Performance metrics Statistical significance of the performance differences *http://www.biochemia-­‐medica.com/content/comparing-­‐groups-­‐statistical-­‐differences-­‐how-­‐choose-­‐right-­‐statistical-­‐test mi      t1      t2 t3 t4 t12 t13 t14      t23      t24      t34      t123      t124      t134      t234      t1234 One  sample Two  samples Three  or  more   samples Drawn  from   a  normal   distribution? Drawn  from   a  normal   distribution? Drawn  from   a  normal   distribution? One sample t-­‐test Wilcoxon rank  sum test Paired   samples? Equal variance? Paired t-­‐test Unaired t-­‐test Welch’s corrected unpaired  test Wilcoxon’s matched pairs  test Mann-­‐Whitney test Paired   samples? Paired   samples? Repeated measures one-­‐way  ANOVA Paired   samples? One-­‐way   ANOVA Friedman test Kruskal-­‐Wallis test Yes Yes Yes Yes Yes Yes Yes Yes No No No No No No No No Population
66 5. Test Statistical Significance of Differences Performance metrics Statistical significance of the performance differences *http://www.biochemia-­‐medica.com/content/comparing-­‐groups-­‐statistical-­‐differences-­‐how-­‐choose-­‐right-­‐statistical-­‐test mi      t1      t2 t3 t4 t12 t13 t14      t23      t24      t34      t123      t124      t134      t234      t1234 Population One  sample Two  samples Three  or  more   samples Drawn  from   a  normal   distribution? Drawn  from   a  normal   distribution? Drawn  from   a  normal   distribution? One sample t-­‐test Wilcoxon rank  sum test Paired   samples? Equal variance? Paired t-­‐test Unaired t-­‐test Welch’s corrected unpaired  test Wilcoxon’s matched pairs  test Mann-­‐Whitney test Paired   samples? Paired   samples? Repeated measures one-­‐way  ANOVA Paired   samples? One-­‐way   ANOVA Friedman test Kruskal-­‐Wallis test Yes Yes Yes Yes Yes Yes Yes Yes No No No No No No No No
67 5. Test Statistical Significance of Differences Performance metrics Statistical significance of the performance differences *http://www.biochemia-­‐medica.com/content/comparing-­‐groups-­‐statistical-­‐differences-­‐how-­‐choose-­‐right-­‐statistical-­‐test mi      t1      t2 t3 t4 t12 t13 t14      t23      t24      t34      t123      t124      t134      t234      t1234 Three  or  more   samples Drawn  from   a  normal   distribution? Paired   samples? Paired   samples? Repeated measures one-­‐way  ANOVA One-­‐way   ANOVA Friedman test Kruskal-­‐Wallis test Yes Yes Yes No No No
68 5. Test Statistical Significance of Differences Performance metrics Statistical significance of the performance differences *http://www.biochemia-­‐medica.com/content/comparing-­‐groups-­‐statistical-­‐differences-­‐how-­‐choose-­‐right-­‐statistical-­‐test mi      t1      t2 t3 t4 t12 t13 t14      t23      t24      t34      t123      t124      t134      t234      t1234 Three  or  more   samples Drawn  from   a  normal   distribution? Paired   samples? Paired   samples? Repeated measures one-­‐way  ANOVA One-­‐way   ANOVA Friedman test Kruskal-­‐Wallis test Yes Yes Yes No No No
69 5. Test Statistical Significance of Differences Performance metrics Statistical significance of the performance differences *http://www.biochemia-­‐medica.com/content/comparing-­‐groups-­‐statistical-­‐differences-­‐how-­‐choose-­‐right-­‐statistical-­‐test mi      t1      t2 t3 t4 t12 t13 t14      t23      t24      t34      t123      t124      t134      t234      t1234 Three  or  more   samples Drawn  from   a  normal   distribution? Paired   samples? Paired   samples? Repeated measures one-­‐way  ANOVA One-­‐way   ANOVA Friedman test Kruskal-­‐Wallis test Yes Yes Yes No No No
70 5. Test Statistical Significance of Differences Performance metrics Statistical significance of the performance differences RQ1:  Does  the  application  of  different  modeling  practices  have  significant  impact  on  the   duration of  a  BP  instance  execution?  
71 5. Test Statistical Significance of Differences Performance metrics Statistical significance of the performance differences RQ1:  Does  the  application  of  different  modeling  practices  have  significant  impact  on  the   duration of  a  BP  instance  execution?  
72 5. Test Statistical Significance of Differences Performance metrics Statistical significance of the performance differences RQ1:  Does  the  application  of  different  modeling  practices  have  significant  impact  on  the   duration of  a  BP  instance  execution?   YES!
73 5. Test Statistical Significance of Differences Performance metrics Statistical significance of the performance differences RQ1:  Does  the  application  of  different  modeling  practices  have  significant  impact  on  the   duration of  a  BP  instance  execution?   YES! improvement  possibilities  to  BPMS  vendors
74 6. Rank the Performance of Transformed Models Statistical significance of the performance differences RQ2:  Is  there  a  total  order between  semantically  equivalent  but  structurally  different   models,  when  ranked  according  to  their  performance?  
75 6. Rank the Performance of Transformed Models Statistical significance of the performance differences RQ2:  Is  there  a  total  order between  semantically  equivalent  but  structurally  different   models,  when  ranked  according  to  their  performance?   NO!
76 6. Rank the Performance of Transformed Models Statistical significance of the performance differences RQ2:  Is  there  a  total  order between  semantically  equivalent  but  structurally  different   models,  when  ranked  according  to  their  performance?   NO! opportunity  to  identify  optimization  rules  
78 6. Rank the Performance of Transformed Models Statistical significance of the performance differences RQ2:  Is  there  a  total  order between  semantically  equivalent  but  structurally  different   models,  when  ranked  according  to  their  performance?   NO! opportunity  to  identify  optimization  rules  
78 6. Rank the Performance of Transformed Models Statistical significance of the performance differences RQ2:  Is  there  a  total  order between  semantically  equivalent  but  structurally  different   models,  when  ranked  according  to  their  performance?   NO! opportunity  to  identify  optimization  rules  
79 Performance  Variability Acceptability  index 𝑨𝑰 𝑨, 𝑩 =   𝒎 𝑩 − 𝒎(𝑨) 𝒘 𝑩 + 𝒘(𝑨) *Sengupta,  A.,  Pal,  T.K.:  On  comparing  interval  numbers.  European  Journal  of  Operational  Research  127(1),  28–43  (2000)   𝐴 = [𝑎𝑙, 𝑎𝑟] 𝐵 = [𝑏𝑙, 𝑏𝑟] 95%  confidence  interval of  the  duration 𝑚 𝐴 𝑚 𝐵 average  duration  of model’s  instances w 𝐴 w 𝐵 half-­‐width  of  the confidence  interval 𝐴 𝐵 initial  model  (mi) transformed  model  (t)
80 Performance  Variability Acceptability  index 𝑨𝑰 𝑨, 𝑩 =   𝒎 𝑩 − 𝒎(𝑨) 𝒘 𝑩 + 𝒘(𝑨) *Sengupta,  A.,  Pal,  T.K.:  On  comparing  interval  numbers.  European  Journal  of  Operational  Research  127(1),  28–43  (2000)   𝐴 = [𝑎𝑙, 𝑎𝑟] 𝐵 = [𝑏𝑙, 𝑏𝑟] 95%  confidence  interval of  the  duration 𝑚 𝐴 𝑚 𝐵 average  duration  of model’s  instances w 𝐴 w 𝐵 half-­‐width  of  the confidence  interval 𝐴 𝐵 initial  model  (mi) transformed  model  (t) -­‐1 1𝐴𝐼 overlapping intervals
81 Performance  Variability Acceptability  index 𝑨𝑰 𝑨, 𝑩 =   𝒎 𝑩 − 𝒎(𝑨) 𝒘 𝑩 + 𝒘(𝑨) *Sengupta,  A.,  Pal,  T.K.:  On  comparing  interval  numbers.  European  Journal  of  Operational  Research  127(1),  28–43  (2000)   𝐴 = [𝑎𝑙, 𝑎𝑟] 𝐵 = [𝑏𝑙, 𝑏𝑟] 95%  confidence  interval of  the  duration 𝑚 𝐴 𝑚 𝐵 average  duration  of model’s  instances w 𝐴 w 𝐵 half-­‐width  of  the confidence  interval 𝐴 𝐵 initial  model  (mi) transformed  model  (t) -­‐1 1𝐴𝐼 transformed  model is  faster overlapping intervals
82 Performance  Variability Acceptability  index 𝑨𝑰 𝑨, 𝑩 =   𝒎 𝑩 − 𝒎(𝑨) 𝒘 𝑩 + 𝒘(𝑨) *Sengupta,  A.,  Pal,  T.K.:  On  comparing  interval  numbers.  European  Journal  of  Operational  Research  127(1),  28–43  (2000)   𝐴 = [𝑎𝑙, 𝑎𝑟] 𝐵 = [𝑏𝑙, 𝑏𝑟] 95%  confidence  interval of  the  duration 𝑚 𝐴 𝑚 𝐵 average  duration  of model’s  instances w 𝐴 w 𝐵 half-­‐width  of  the confidence  interval 𝐴 𝐵 initial  model  (mi) transformed  model  (t) -­‐1 1𝐴𝐼 initial  model is  faster transformed  model is  faster overlapping intervals
11.# 12.# 8.# 13.# 9.# 5.# 10.# 2.# 12.# 7.# 3.# 9.# 6.# 4.# 1.# 7.# 7.# 12.# 8.# 3.# 9.# 4.# 8.# 5.# 10.# 3.# 1.# 6.# 6.# 2.# !32$ !30$ !28$ !26$ !24$ !22$ !20$ !18$ !16$ !14$ !12$ !10$ !8$ !6$ !4$ !2$ 0$ 2$ t1$ t2$ t3$ t4$ t12$ t13$ t14$ t23$ t24$ t34$ t123$ t124$ t134$ t234$ t1234$ Acceptability#Index# Parallel#Control#Flow#(EX1_PCF)# Trial$1$!$Ac2vi2$ Trial$2$!$Ac2vi2$ Trial$3$!$Ac2vi2$ Trial$1$!$Camunda$ Trial$2$!$Camunda$ Trial$3$!$Camunda$ Ac2vi2$Ranks$1.#to#14.# Camunda$Ranks$1.#to#12.# Overlapping$$ confidence$intervals$ 83 Performance  Variability
11.# 12.# 8.# 13.# 9.# 5.# 10.# 2.# 12.# 7.# 3.# 9.# 6.# 4.# 1.# 7.# 7.# 12.# 8.# 3.# 9.# 4.# 8.# 5.# 10.# 3.# 1.# 6.# 6.# 2.# !32$ !30$ !28$ !26$ !24$ !22$ !20$ !18$ !16$ !14$ !12$ !10$ !8$ !6$ !4$ !2$ 0$ 2$ t1$ t2$ t3$ t4$ t12$ t13$ t14$ t23$ t24$ t34$ t123$ t124$ t134$ t234$ t1234$ Acceptability#Index# Parallel#Control#Flow#(EX1_PCF)# Trial$1$!$Ac2vi2$ Trial$2$!$Ac2vi2$ Trial$3$!$Ac2vi2$ Trial$1$!$Camunda$ Trial$2$!$Camunda$ Trial$3$!$Camunda$ Ac2vi2$Ranks$1.#to#14.# Camunda$Ranks$1.#to#12.# Overlapping$$ confidence$intervals$ 84 Performance  Variability
11.# 12.# 8.# 13.# 9.# 5.# 10.# 2.# 12.# 7.# 3.# 9.# 6.# 4.# 1.# 7.# 7.# 12.# 8.# 3.# 9.# 4.# 8.# 5.# 10.# 3.# 1.# 6.# 6.# 2.# !32$ !30$ !28$ !26$ !24$ !22$ !20$ !18$ !16$ !14$ !12$ !10$ !8$ !6$ !4$ !2$ 0$ 2$ t1$ t2$ t3$ t4$ t12$ t13$ t14$ t23$ t24$ t34$ t123$ t124$ t134$ t234$ t1234$ Acceptability#Index# Parallel#Control#Flow#(EX1_PCF)# Trial$1$!$Ac2vi2$ Trial$2$!$Ac2vi2$ Trial$3$!$Ac2vi2$ Trial$1$!$Camunda$ Trial$2$!$Camunda$ Trial$3$!$Camunda$ Ac2vi2$Ranks$1.#to#14.# Camunda$Ranks$1.#to#12.# Overlapping$$ confidence$intervals$ 85 Performance  Variability
11.# 12.# 8.# 13.# 9.# 5.# 10.# 2.# 12.# 7.# 3.# 9.# 6.# 4.# 1.# 7.# 7.# 12.# 8.# 3.# 9.# 4.# 8.# 5.# 10.# 3.# 1.# 6.# 6.# 2.# !32$ !30$ !28$ !26$ !24$ !22$ !20$ !18$ !16$ !14$ !12$ !10$ !8$ !6$ !4$ !2$ 0$ 2$ t1$ t2$ t3$ t4$ t12$ t13$ t14$ t23$ t24$ t34$ t123$ t124$ t134$ t234$ t1234$ Acceptability#Index# Parallel#Control#Flow#(EX1_PCF)# Trial$1$!$Ac2vi2$ Trial$2$!$Ac2vi2$ Trial$3$!$Ac2vi2$ Trial$1$!$Camunda$ Trial$2$!$Camunda$ Trial$3$!$Camunda$ Ac2vi2$Ranks$1.#to#14.# Camunda$Ranks$1.#to#12.# Overlapping$$ confidence$intervals$ 86 1.3.5 Parallel_R1R2R3R4 1.3.5 Start Empty ST 1.3.5.1 Empty ST 1.3.5.2 Empty ST 1.3.5.3 Empty ST 1.3.5.4 Empty ST 1.3.5.5 1.3.5 End IG 1.3.5.1 t1234 Performance  Variability
11.# 12.# 8.# 13.# 9.# 5.# 10.# 2.# 12.# 7.# 3.# 9.# 6.# 4.# 1.# 7.# 7.# 12.# 8.# 3.# 9.# 4.# 8.# 5.# 10.# 3.# 1.# 6.# 6.# 2.# !32$ !30$ !28$ !26$ !24$ !22$ !20$ !18$ !16$ !14$ !12$ !10$ !8$ !6$ !4$ !2$ 0$ 2$ t1$ t2$ t3$ t4$ t12$ t13$ t14$ t23$ t24$ t34$ t123$ t124$ t134$ t234$ t1234$ Acceptability#Index# Parallel#Control#Flow#(EX1_PCF)# Trial$1$!$Ac2vi2$ Trial$2$!$Ac2vi2$ Trial$3$!$Ac2vi2$ Trial$1$!$Camunda$ Trial$2$!$Camunda$ Trial$3$!$Camunda$ Ac2vi2$Ranks$1.#to#14.# Camunda$Ranks$1.#to#12.# Overlapping$$ confidence$intervals$ 87 1.3.5 Parallel_R1R2R3R4 1.3.5 Start Empty ST 1.3.5.1 Empty ST 1.3.5.2 Empty ST 1.3.5.3 Empty ST 1.3.5.4 Empty ST 1.3.5.5 1.3.5 End IG 1.3.5.1 t1234 1.3.2 Parallel_R1R2R4 1.3.2 Start Empty ST 1.3.2.1 Empty ST 1.3.2.2 Empty ST 1.3.2.3 Empty ST 1.3.2.4 Empty ST 1.3.2.5 PG 1.3.2.1 1.3.2 End t124 Performance  Variability
Performance Variability 5.# 5.# 6.# 5.# 3.# 5.# 3.# 5.# 2.# 5.# 4.# 1.# 4.# 4.# 2.# 4.# 5.# 7.# 6.# 2.# 4.# 3.# 5.# 2.# 5.# 2.# 1.# 3.# 2.# 1.# !8# !7# !6# !5# !4# !3# !2# !1# 0# 1# 2# t1# t2# t3# t4# t12# t13# t14# t23# t24# t34# t123# t124# t134# t234# t1234# Acceptability#Index# Exclusive#Control#Flow#(EX2_ECF)# Trial#1#!#Ac4vi4# Trial#2#!#Ac4vi4# Trial#3#!#Ac4vi4# Trial#1#!#Camunda# Trial#2#!#Camunda# Trial#3#!#Camunda# Ac4vi4#Ranks#1.#to#6.# Camunda#Ranks#1.#to#7.# Overlapping## confidence#intervals# 88
Performance Variability 5.# 5.# 6.# 5.# 3.# 5.# 3.# 5.# 2.# 5.# 4.# 1.# 4.# 4.# 2.# 4.# 5.# 7.# 6.# 2.# 4.# 3.# 5.# 2.# 5.# 2.# 1.# 3.# 2.# 1.# !8# !7# !6# !5# !4# !3# !2# !1# 0# 1# 2# t1# t2# t3# t4# t12# t13# t14# t23# t24# t34# t123# t124# t134# t234# t1234# Acceptability#Index# Exclusive#Control#Flow#(EX2_ECF)# Trial#1#!#Ac4vi4# Trial#2#!#Ac4vi4# Trial#3#!#Ac4vi4# Trial#1#!#Camunda# Trial#2#!#Camunda# Trial#3#!#Camunda# Ac4vi4#Ranks#1.#to#6.# Camunda#Ranks#1.#to#7.# Overlapping## confidence#intervals# 89 3.3.2 Exclusive_R1R2R4 3.3.2 Start Empty ST 3.3.2.2 Empty ST 3.3.2.5 EG 3.3.2.1 Empty ST 3.3.2.6 3.3.2 End Empty ST 3.3.2.3 Empty ST 3.3.2.4 Generate ST 3.3.2.1 a==3a==0 a == 1 a == 2 t124
Performance Variability 5.# 5.# 6.# 5.# 3.# 5.# 3.# 5.# 2.# 5.# 4.# 1.# 4.# 4.# 2.# 4.# 5.# 7.# 6.# 2.# 4.# 3.# 5.# 2.# 5.# 2.# 1.# 3.# 2.# 1.# !8# !7# !6# !5# !4# !3# !2# !1# 0# 1# 2# t1# t2# t3# t4# t12# t13# t14# t23# t24# t34# t123# t124# t134# t234# t1234# Acceptability#Index# Exclusive#Control#Flow#(EX2_ECF)# Trial#1#!#Ac4vi4# Trial#2#!#Ac4vi4# Trial#3#!#Ac4vi4# Trial#1#!#Camunda# Trial#2#!#Camunda# Trial#3#!#Camunda# Ac4vi4#Ranks#1.#to#6.# Camunda#Ranks#1.#to#7.# Overlapping## confidence#intervals# 90 3.3.3 Exclusive_R1R3R4 3.3.3 Start Empty ST 3.3.3.2 Empty ST 3.3.3.5 Empty ST 3.3.3.6 3.3.3 End Empty ST 3.3.3.3 Empty ST 3.3.3.4 Generate ST 3.3.3.1 IG 3.3.3.1 IG 3.3.3.2 IG 3.3.3.3 a==1a==2a==3a==0 a == 0 || a == 1 a == 2 || a == 3 3.3.2 Exclusive_R1R2R4 3.3.2 Start Empty ST 3.3.2.2 Empty ST 3.3.2.5 EG 3.3.2.1 Empty ST 3.3.2.6 3.3.2 End Empty ST 3.3.2.3 Empty ST 3.3.2.4 Generate ST 3.3.2.1 a==3a==0 a == 1 a == 2 t124 t1234
Performance  Variability 9.# 10.# 4.# 11.# 6.# 3.# 7.# 2.# 8.# 3.# 1.# 5.# 3.# 2.# 1.# 9.# 10.# 6.# 11.# 8.# 4.# 9.# 4.# 9.# 5.# 2.# 7.# 3.# 3.# 1.# !50$ !48$ !46$ !44$ !42$ !40$ !38$ !36$ !34$ !32$ !30$ !28$ !26$ !24$ !22$ !20$ !18$ !16$ !14$ !12$ !10$ !8$ !6$ !4$ !2$ 0$ 2$ t1$ t2$ t3$ t4$ t12$ t13$ t14$ t23$ t24$ t34$ t123$ t124$ t134$ t234$ t1234$ Acceptability#Index# Inclusive#Control#Flow#(EX3_ICF)# Trial$1$!$Ac3vi3$ Trial$2$!$Ac3vi3$ Trial$3$!$Ac3vi3$ Trial$1$!$Camunda$ Trial$2$!$Camunda$ Trial$3$!$Camunda$ Ac3vi3$Ranks$1.#to#11.# Camunda$Ranks$1.#to#12.# Overlapping$$ confidence$intervals$ 91
Performance  Variability 9.# 10.# 4.# 11.# 6.# 3.# 7.# 2.# 8.# 3.# 1.# 5.# 3.# 2.# 1.# 9.# 10.# 6.# 11.# 8.# 4.# 9.# 4.# 9.# 5.# 2.# 7.# 3.# 3.# 1.# !50$ !48$ !46$ !44$ !42$ !40$ !38$ !36$ !34$ !32$ !30$ !28$ !26$ !24$ !22$ !20$ !18$ !16$ !14$ !12$ !10$ !8$ !6$ !4$ !2$ 0$ 2$ t1$ t2$ t3$ t4$ t12$ t13$ t14$ t23$ t24$ t34$ t123$ t124$ t134$ t234$ t1234$ Acceptability#Index# Inclusive#Control#Flow#(EX3_ICF)# Trial$1$!$Ac3vi3$ Trial$2$!$Ac3vi3$ Trial$3$!$Ac3vi3$ Trial$1$!$Camunda$ Trial$2$!$Camunda$ Trial$3$!$Camunda$ Ac3vi3$Ranks$1.#to#11.# Camunda$Ranks$1.#to#12.# Overlapping$$ confidence$intervals$ 92
Performance  Variability 9.# 10.# 4.# 11.# 6.# 3.# 7.# 2.# 8.# 3.# 1.# 5.# 3.# 2.# 1.# 9.# 10.# 6.# 11.# 8.# 4.# 9.# 4.# 9.# 5.# 2.# 7.# 3.# 3.# 1.# !50$ !48$ !46$ !44$ !42$ !40$ !38$ !36$ !34$ !32$ !30$ !28$ !26$ !24$ !22$ !20$ !18$ !16$ !14$ !12$ !10$ !8$ !6$ !4$ !2$ 0$ 2$ t1$ t2$ t3$ t4$ t12$ t13$ t14$ t23$ t24$ t34$ t123$ t124$ t134$ t234$ t1234$ Acceptability#Index# Inclusive#Control#Flow#(EX3_ICF)# Trial$1$!$Ac3vi3$ Trial$2$!$Ac3vi3$ Trial$3$!$Ac3vi3$ Trial$1$!$Camunda$ Trial$2$!$Camunda$ Trial$3$!$Camunda$ Ac3vi3$Ranks$1.#to#11.# Camunda$Ranks$1.#to#12.# Overlapping$$ confidence$intervals$ 93
Performance  Variability 9.# 10.# 4.# 11.# 6.# 3.# 7.# 2.# 8.# 3.# 1.# 5.# 3.# 2.# 1.# 9.# 10.# 6.# 11.# 8.# 4.# 9.# 4.# 9.# 5.# 2.# 7.# 3.# 3.# 1.# !50$ !48$ !46$ !44$ !42$ !40$ !38$ !36$ !34$ !32$ !30$ !28$ !26$ !24$ !22$ !20$ !18$ !16$ !14$ !12$ !10$ !8$ !6$ !4$ !2$ 0$ 2$ t1$ t2$ t3$ t4$ t12$ t13$ t14$ t23$ t24$ t34$ t123$ t124$ t134$ t234$ t1234$ Acceptability#Index# Inclusive#Control#Flow#(EX3_ICF)# Trial$1$!$Ac3vi3$ Trial$2$!$Ac3vi3$ Trial$3$!$Ac3vi3$ Trial$1$!$Camunda$ Trial$2$!$Camunda$ Trial$3$!$Camunda$ Ac3vi3$Ranks$1.#to#11.# Camunda$Ranks$1.#to#12.# Overlapping$$ confidence$intervals$ 94
Performance  Variability 9.# 10.# 4.# 11.# 6.# 3.# 7.# 2.# 8.# 3.# 1.# 5.# 3.# 2.# 1.# 9.# 10.# 6.# 11.# 8.# 4.# 9.# 4.# 9.# 5.# 2.# 7.# 3.# 3.# 1.# !50$ !48$ !46$ !44$ !42$ !40$ !38$ !36$ !34$ !32$ !30$ !28$ !26$ !24$ !22$ !20$ !18$ !16$ !14$ !12$ !10$ !8$ !6$ !4$ !2$ 0$ 2$ t1$ t2$ t3$ t4$ t12$ t13$ t14$ t23$ t24$ t34$ t123$ t124$ t134$ t234$ t1234$ Acceptability#Index# Inclusive#Control#Flow#(EX3_ICF)# Trial$1$!$Ac3vi3$ Trial$2$!$Ac3vi3$ Trial$3$!$Ac3vi3$ Trial$1$!$Camunda$ Trial$2$!$Camunda$ Trial$3$!$Camunda$ Ac3vi3$Ranks$1.#to#11.# Camunda$Ranks$1.#to#12.# Overlapping$$ confidence$intervals$ 95 2.3.2 Inclusive_R1R2R4 (Copy) 2.3.2 Start Empty ST 2.3.2.2 Empty ST 2.3.2.5 2.3.2 End Empty ST 2.3.2.3 Empty ST 2.3.2.4 Generate ST 2.3.2.1 IG 2.3.2.1 a==0 b == 0 d==0 c == 0 t1234
Performance  Variability 9.# 10.# 4.# 11.# 6.# 3.# 7.# 2.# 8.# 3.# 1.# 5.# 3.# 2.# 1.# 9.# 10.# 6.# 11.# 8.# 4.# 9.# 4.# 9.# 5.# 2.# 7.# 3.# 3.# 1.# !50$ !48$ !46$ !44$ !42$ !40$ !38$ !36$ !34$ !32$ !30$ !28$ !26$ !24$ !22$ !20$ !18$ !16$ !14$ !12$ !10$ !8$ !6$ !4$ !2$ 0$ 2$ t1$ t2$ t3$ t4$ t12$ t13$ t14$ t23$ t24$ t34$ t123$ t124$ t134$ t234$ t1234$ Acceptability#Index# Inclusive#Control#Flow#(EX3_ICF)# Trial$1$!$Ac3vi3$ Trial$2$!$Ac3vi3$ Trial$3$!$Ac3vi3$ Trial$1$!$Camunda$ Trial$2$!$Camunda$ Trial$3$!$Camunda$ Ac3vi3$Ranks$1.#to#11.# Camunda$Ranks$1.#to#12.# Overlapping$$ confidence$intervals$ 96 2.3.2 Inclusive_R1R2R4 (Copy) 2.3.2 Start Empty ST 2.3.2.2 Empty ST 2.3.2.5 2.3.2 End Empty ST 2.3.2.3 Empty ST 2.3.2.4 Generate ST 2.3.2.1 IG 2.3.2.1 a==0 b == 0 d==0 c == 0 2.2.1 Inclusive_R1R2 (Copy) 2.2.1 Start Empty ST 2.2.1.2 Empty ST 2.2.1.5 2.2.1 End Empty ST 2.2.1.3 Empty ST 2.2.1.4 Generate ST 2.2.1.1 IG 2.2.1.1 IG 2.2.1.2 a==0d==0 b == 0 c == 0 t123 t1234
Avoid  Inclusive  Gateways   97 Modeling  practices  and  performance
Avoid  Inclusive  Gateways   98 Modeling  practices  and  performance EX3_ICFECF 2.2 2.5 Empty ST 2.6 2 End 2.3 2.4 G 2.3 G 2.5 EG 2.6 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0
Avoid  Inclusive  Gateways   99 Modeling  practices  and  performance Use  inclusive  gateways EX3_ICFECF 2.2 2.5 Empty ST 2.6 2 End 2.3 2.4 G 2.3 G 2.5 EG 2.6 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0
Avoid  Inclusive  Gateways   100 Modeling  practices  and  performance Use  inclusive  gateways EX3_ICFECF 2.2 2.5 Empty ST 2.6 2 End 2.3 2.4 G 2.3 G 2.5 EG 2.6 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 2.1.Inclusive_Multiple 2.1 Start Empty ST 2.1.2 Empty ST 2.1.5 2.1 End Empty ST 2.1.3 Empty ST 2.1.4 Generate ST 2.1.1 IG 2.1.1 IG 2.1.2 IG 2.1.4 IG 2.1.3 IG 2.1.5 IG 2.1.6 a==0||b==0c==0||d==0 a==0b==0c==0d==0 First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0
Avoid  Inclusive  Gateways   101 Modeling  practices  and  performance Use  inclusive  gateways EX3_ICFECF 2.2 2.5 Empty ST 2.6 2 End 2.3 2.4 G 2.3 G 2.5 EG 2.6 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 2.1.Inclusive_Multiple 2.1 Start Empty ST 2.1.2 Empty ST 2.1.5 2.1 End Empty ST 2.1.3 Empty ST 2.1.4 Generate ST 2.1.1 IG 2.1.1 IG 2.1.2 IG 2.1.4 IG 2.1.3 IG 2.1.5 IG 2.1.6 a==0||b==0c==0||d==0 a==0b==0c==0d==0 Camunda 2.76  ms ± 0.08  ms Camunda 2.02  ms ± 0.03  msFirst models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0
Avoid  Inclusive  Gateways   102 Modeling  practices  and  performance Use  inclusive  gateways EX3_ICFECF 2.2 2.5 Empty ST 2.6 2 End 2.3 2.4 G 2.3 G 2.5 EG 2.6 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 2.1.Inclusive_Multiple 2.1 Start Empty ST 2.1.2 Empty ST 2.1.5 2.1 End Empty ST 2.1.3 Empty ST 2.1.4 Generate ST 2.1.1 IG 2.1.1 IG 2.1.2 IG 2.1.4 IG 2.1.3 IG 2.1.5 IG 2.1.6 a==0||b==0c==0||d==0 a==0b==0c==0d==0 Camunda 2.76  ms ± 0.08  ms Camunda 2.02  ms ± 0.03  msFirst models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 Activiti   29.87ms  ± 0.30  ms Activiti   11.66  ms ± 0.16  ms
Avoid  Inclusive  Gateways   103 Modeling  practices  and  performance Use  inclusive  gateways EX3_ICFECF 2.2 2.5 Empty ST 2.6 2 End 2.3 2.4 G 2.3 G 2.5 EG 2.6 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 2.1.Inclusive_Multiple 2.1 Start Empty ST 2.1.2 Empty ST 2.1.5 2.1 End Empty ST 2.1.3 Empty ST 2.1.4 Generate ST 2.1.1 IG 2.1.1 IG 2.1.2 IG 2.1.4 IG 2.1.3 IG 2.1.5 IG 2.1.6 a==0||b==0c==0||d==0 a==0b==0c==0d==0 Camunda 2.76  ms ± 0.08  ms Camunda 2.02  ms ± 0.03  msFirst models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 R3_Parallel_Alternative R3.PG Start Empty ST R3.PG.1 Empty ST R3.PG.2 Empty ST R3.PG.3 Empty ST R3.PG.4 Empty ST R3.PG.5 R3.PG EndIG R3.PG.1 IG R3.PG.2 IG R3.PG.4 IG R3.PG.3 IG R3.PG.5 IG R3.PG.6 Activiti   29.87ms  ± 0.30  ms Activiti   11.66  ms ± 0.16  ms Activiti   26.04  ms ± 0.21  ms Activiti   19.57  ms ± 0.18  ms
Avoid  Inclusive  Gateways   104 Modeling  practices  and  performance Use  inclusive  gateways EX3_ICFECF 2.2 2.5 Empty ST 2.6 2 End 2.3 2.4 G 2.3 G 2.5 EG 2.6 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 2.1.Inclusive_Multiple 2.1 Start Empty ST 2.1.2 Empty ST 2.1.5 2.1 End Empty ST 2.1.3 Empty ST 2.1.4 Generate ST 2.1.1 IG 2.1.1 IG 2.1.2 IG 2.1.4 IG 2.1.3 IG 2.1.5 IG 2.1.6 a==0||b==0c==0||d==0 a==0b==0c==0d==0 Camunda 2.76  ms ± 0.08  ms Camunda 2.02  ms ± 0.03  msFirst models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 Camunda 2.51  ms ± 0.05  ms Camunda 2.58  ms ± 0.05  ms R3_Parallel_Alternative R3.PG Start Empty ST R3.PG.1 Empty ST R3.PG.2 Empty ST R3.PG.3 Empty ST R3.PG.4 Empty ST R3.PG.5 R3.PG EndIG R3.PG.1 IG R3.PG.2 IG R3.PG.4 IG R3.PG.3 IG R3.PG.5 IG R3.PG.6 Activiti   29.87ms  ± 0.30  ms Activiti   11.66  ms ± 0.16  ms Activiti   26.04  ms ± 0.21  ms Activiti   19.57  ms ± 0.18  ms
Use  as  Few  Elements  as  Possibile 105 Modeling  practices  and  performance
Use  as  Few  Elements  as  Possible 106 Modeling  practices  and  performance
Use  as  Few  Elements  as  Possible 107 Modeling  practices  and  performance
Use  as  Few  Elements  as  Possible 108 Modeling  practices  and  performance
Minimize  the  routing  paths  per  element Model  as  structured  as  possible 109 Modeling  practices  and  performance
Minimize  the  routing  paths  per  element Model  as  structured  as  possible 110 1.3.5 Parallel_R1R2R3R4 1.3.5 Start Empty ST 1.3.5.1 Empty ST 1.3.5.2 Empty ST 1.3.5.3 Empty ST 1.3.5.4 Empty ST 1.3.5.5 1.3.5 End IG 1.3.5.1 t124 t1234 Best  performing  models Modeling  practices  and  performance 1.3.2 Start Empty ST 1.3.2.1 Empty ST 1.3.2.2 Empty ST 1.3.2.3 Empty ST 1.3.2.4 Empty ST 1.3.2.5 PG 1.3.2.1 1.3.2 End
Conclusions 111 Modeling  is  a  discretional  decision  of  the  modeler!!!
Conclusions 112 Our  ultimate  goal:   Take  the  model  and  transform  it  to  a  better  performing  but  semantically   equivalent  model Modeling  is  a  discretional  decision  of  the  modeler!!!
Conclusions 113 Our  ultimate  goal:   Take  the  model  and  transform  it  to  a  better  performing  but  semantically   equivalent  model Modeling  is  a  discretional  decision  of  the  modeler!!! Our  challenge:   Define  optimization  rules  to  obtain  the  better  performing  model  
Conclusions 114 in  milliseconds in  milliseconds
Conclusions 115 ~𝟏𝟕% ~𝟏𝟓% ~𝟑𝟔% ~𝟒𝟎% ~𝟑𝟓% ~𝟔𝟕% New  automatic  optimization  opportunity? in  milliseconds in  milliseconds
On  the   Performance  Overhead of BPMN  Modeling  Practices   ana.ivanchikj@usi.ch
Back-­‐up  slides ana.ivanchikj@usi.ch
118 empty  tasks script  task script  task FULLY  AUTOMATED 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) First models v4 EX1_PCF EX2_E 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2 Empty ST 2 EG 2.1 Empty ST 2 Empty ST 2 EG 2.2 EG 2.4 EG EG Generate ST 2.1 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 Parallel First models v4 EX1_PCF EX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 3 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 Exclusive Inclusive
119 Model  ranking Dunn’s  test  -­‐ the  H0 is  that  the  probability  of  observing  a  randomly  selected  value  from  the   first  sample  that  is  larger  than  a  randomly  selected  value  from  the  second  sample  equals   one  half,  i.e.,  no  sample  dominates  the  other =>  we  assign  the  same  rank. Rejecting  the  H0,  implies  that  the  first  sample  is  dominated  by  the  second  sample =>  we   assign  different  ranks. Base-­‐case  rank  -­‐ the  sum of  the  assigned  ranks  in  each performed  trial (what  we  show  in   the  table). Sensitivity  analysis  -­‐ we  test  the  sensitivity  of  the  order  of  the  performance  of  the  executed   models  as  per  the  base-­‐case  rank  on  the  the  ranks  from  the  individual  trials.  We  use  a   deterministic  one-­‐at-­‐a-­‐time,  also  known  as  one-­‐side,  sensitivity  analysis.
120 -­‐ the  WfMS,  the  DB  and  Faban,  are  all  deployed  in  Docker  images  on  dedicated  servers   using  the  Docker  Engine  1.9.1  and  Ubuntu 14.04.3  LTS  (GNU/Linux  3.13.0-­‐40-­‐generic   x86  64)  as  OS.   -­‐ they  interact  through  two  networks of  10Gbit/s  each,  one  dedicated  to  the   communication  between  the  WfMS and  the  DB  and  the  other  one  dedicated  to  other   interactions  (e.g.,  issuing  the  load).   -­‐ The  WfMS runs  on  a  server with  64  Cores  (2  threads)  and  a  clock  speed  of  1’400MHz   mounting  128GB  of  RAM  and  a  magnetic  disk  with  15’000  rpm.   -­‐ The  DB runs  on  a  server with  64  Cores  (2  threads)  and  a  clock  speed  of  2’300MHz   mounting  128GB  of  RAM  and  a  SSD  SATA  disk.   -­‐ Faban’s Load  Drivers  are  placed  on  three  servers:  one  with  64  Cores  (2  threads)  and  a   clock  speed  of  2’300MHz  mounting  128GB  of  RAM,  the  second  with  48  Cores  (2   threads)  and  a  clock  speed  of  2’000MHz  mounting  128GB  of  RAM,  and  the  third  with   12  Cores  (1  thread)  at  800MHz  mounting  64GB  of  RAM.   Benchflow Environment  Setup

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On the Performance Overhead of BPMN Modeling Practices

  • 1. On  the   Performance  Overhead  of BPMN  Modeling  Practices   Ana  Ivanchikj Vincenzo  Ferme Cesare  Pautasso University  of  Lugano  (USI) Switzerland
  • 5. 5 BPMN  Expressiveness BPMN  Standard Model’s  Semantics Model’s  Understandability
  • 9. 9 Structural  Differences B A C B A C Semantical  Equivalence case  id trace 1 ABC 2 ACB 3 ABC …. ….
  • 10. 10 Structural  Differences B A C B A C Semantical  Equivalence case  id trace 1 ABC 2 ACB 3 ABC …. …. Performance  Equivalence
  • 11. 11 Structural  Differences B A C B A C Semantical  Equivalence case  id trace 1 ABC 2 ACB 3 ABC …. …. Performance  Equivalence
  • 12. 12 Research  Questions RQ1: Does  the  application  of  different  modeling  practices  have  a   significant  impact  on  the  duration  of  a  BP  instance  execution?  
  • 13. 13 Research  Questions RQ1: Does  the  application  of  different  modeling  practices  have  a   significant  impact  on  the  duration  of  a  BP  instance  execution?  
  • 14. 14 Research  Questions RQ1: Does  the  application  of  different  modeling  practices  have  a   significant  impact  on  the  duration  of  a  BP  instance  execution?  
  • 15. 15 Research  Questions RQ1: Does  the  application  of  different  modeling  practices  have  a   significant  impact  on  the  duration  of  a  BP  instance  execution?  
  • 16. 16 Research  Questions RQ1: Does  the  application  of  different  modeling  practices  have  a   significant  impact  on  the  duration  of  a  BP  instance  execution?   RQ2: Is  there  a  total  order  between  semantically  equivalent  but   structurally  different  models,  when  ranked  according  to  their   performance?  
  • 17. RQ2: Is  there  a  total  order  between  semantically  equivalent  but   structurally  different  models,  when  ranked  according  to  their   performance?   17 Research  Questions RQ1: Does  the  application  of  different  modeling  practices  have  a   significant  impact  on  the  duration  of  a  BP  instance  execution?  
  • 19. 19 Methodology 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) 4. Execute the BPs in EM and Measure Performance 2. Determine Applicable Transformation Rules Transformation rules (R) Applicable combinations of rules (RA) Load function / WfMS Semantically equivalent BP models (TMi) 3. Generate Transformed BP Models i <= z i>z Unsaved diagram Performance metrics 5. Test Statistical Significance of Differences 6. Rank the Performance of Transformed Models Statistical significance of the performance differences RQ1 RQ2
  • 20. 20 Methodology 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) 4. Execute the BPs in EM and Measure Performance 2. Determine Applicable Transformation Rules Transformation rules (R) Applicable combinations of rules (RA) Load function / WfMS Semantically equivalent BP models (TMi) 3. Generate Transformed BP Models i <= z i>z Unsaved diagram Performance metrics 5. Test Statistical Significance of Differences 6. Rank the Performance of Transformed Models Statistical significance of the performance differences RQ1 RQ2 Experiment  definition  and  execution
  • 21. 21 Methodologym 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) 4. Execute the BPs in EM and Measure Performance 2. Determine Applicable Transformation Rules Transformation rules (R) Applicable combinations of rules (RA) Load function / WfMS Semantically equivalent BP models (TMi) 3. Generate Transformed BP Models i <= z i>z Experiment  definition  and  execution
  • 22. 22 Methodology 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) 4. Execute the BPs in EM and Measure Performance 2. Determine Applicable Transformation Rules Transformation rules (R) Applicable combinations of rules (RA) Load function / WfMS Semantically equivalent BP models (TMi) 3. Generate Transformed BP Models i <= z i>z Unsaved diagram Performance metrics 5. Test Statistical Significance of Differences 6. Rank the Performance of Transformed Models Statistical significance of the performance differences RQ1 RQ2 Experiment  definition  and  execution
  • 23. 23 Methodology 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) 4. Execute the BPs in EM and Measure Performance 2. Determine Applicable Transformation Rules Transformation rules (R) Applicable combinations of rules (RA) Load function / WfMS Semantically equivalent BP models (TMi) 3. Generate Transformed BP Models i <= z i>z Unsaved diagram Performance metrics 5. Test Statistical Significance of Differences 6. Rank the Performance of Transformed Models Statistical significance of the performance differences RQ1 RQ2 Experiment  definition  and  execution Results  analysis  and  ranking
  • 24. 24 Methodology Results  analysis  and  ranking Performance metrics 5. Test Statistical Significance of Differences 6. Rank the Performance of Transformed Models Statistical significance of the performance differences RQ1 RQ2
  • 25. 25 Methodology 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) 4. Execute the BPs in EM and Measure Performance 2. Determine Applicable Transformation Rules Transformation rules (R) Applicable combinations of rules (RA) Load function / WfMS Semantically equivalent BP models (TMi) 3. Generate Transformed BP Models i <= z i>z Unsaved diagram Performance metrics 5. Test Statistical Significance of Differences 6. Rank the Performance of Transformed Models Statistical significance of the performance differences RQ1 RQ2 Experiment  definition  and  execution Results  analysis  and  ranking
  • 26. 26 First models v4 EX1_PCF EX2_E 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2 Empty ST 2 EG 2.1 Empty ST 2 Empty ST 2 EG 2.2 EG 2.4 EG EG Generate ST 2.1 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi)
  • 27. 27 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) First models v4 EX1_PCF EX2_E 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2 Empty ST 2 EG 2.1 Empty ST 2 Empty ST 2 EG 2.2 EG 2.4 EG EG Generate ST 2.1 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 minimize  the  routing   paths  per  element match  every  split  with  a   join  of  the  same  type   1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) use  one  start  and   one  end  event  
  • 28. 28 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) First models v4 EX1_PCF EX2_E 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2 Empty ST 2 EG 2.1 Empty ST 2 Empty ST 2 EG 2.2 EG 2.4 EG EG Generate ST 2.1 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 minimize  the  routing   paths  per  element match  every  split  with  a   join  of  the  same  type   1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) use  one  start  and   one  end  event   1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi)
  • 29. 29 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) First models v4 EX1_PCF EX2_E 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2 Empty ST 2 EG 2.1 Empty ST 2 Empty ST 2 EG 2.2 EG 2.4 EG EG Generate ST 2.1 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 minimize  the  routing   paths  per  element match  every  split  with  a   join  of  the  same  type   1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) use  one  start  and   one  end  event   Parallel
  • 30. 30 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) First models v4 EX1_PCF EX2_E 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2 Empty ST 2 EG 2.1 Empty ST 2 Empty ST 2 EG 2.2 EG 2.4 EG EG Generate ST 2.1 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 First models v4 EX1_PCF EX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 3 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 minimize  the  routing   paths  per  element match  every  split  with  a   join  of  the  same  type   1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) use  one  start  and   one  end  event   Parallel Exclusive
  • 31. 31 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) First models v4 EX1_PCF EX2_E 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2 Empty ST 2 EG 2.1 Empty ST 2 Empty ST 2 EG 2.2 EG 2.4 EG EG Generate ST 2.1 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 First models v4 EX1_PCF EX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 3 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 minimize  the  routing   paths  per  element match  every  split  with  a   join  of  the  same  type   1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) use  one  start  and   one  end  event   avoid  OR   gateways   Parallel Exclusive Inclusive
  • 32. 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) r2    Coalesce  Splitsr1 Coalesce  Joins r3    Use  Inclusive  Gateway r4 Use  Implicit  Gateway 32
  • 33. 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) r2    Coalesce  Splitsr1 Coalesce  Joins r3    Use  Inclusive  Gateway r4 Use  Implicit  Gateway 33 Semantics Preserving Transformation Rules!
  • 34. 34 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) r1 Coalesce  Joins
  • 35. r2    Coalesce  Splits 35 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA)
  • 36. r3    Use  Inclusive  Gateway 36 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA)
  • 37. r4 Use  Implicit  Gateway 37 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA)
  • 38. 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) r2    Coalesce  Splitsr1 Coalesce  Joins r3    Use  Inclusive  Gateway r4 Use  Implicit  Gateway 38 Semantics Preserving Transformation Rules!
  • 39. 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) r2    Coalesce  Splitsr1 Coalesce  Joins r3    Use  Inclusive  Gateway r4 Use  Implicit  Gateway 39 Semantics Preserving Transformation Rules! 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA)
  • 40. 1.1.Parallel_Multiple 1.1 Start Empty ST 1.1.1 PG 1.1.1 PG 1.1.2 PG 1.1.4 Empty ST 1.1.2 Empty ST 1.1.3 Empty ST 1.1.4 Empty ST 1.1.5 PG 1.1.3 PG 1.1.5 PG 1.1.6 1.1 End Initial   Model 40
  • 41. 1.1.Parallel_Multiple 1.1 Start Empty ST 1.1.1 PG 1.1.1 PG 1.1.2 PG 1.1.4 Empty ST 1.1.2 Empty ST 1.1.3 Empty ST 1.1.4 Empty ST 1.1.5 PG 1.1.3 PG 1.1.5 PG 1.1.6 1.1 End Initial   Model 41 coalesce   joinst1 t2 t3 use   inclusive   gateway use   implicit gateway t4 coalesce   splits 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA)
  • 42. 1.1.Parallel_Multiple 1.1 Start Empty ST 1.1.1 PG 1.1.1 PG 1.1.2 PG 1.1.4 Empty ST 1.1.2 Empty ST 1.1.3 Empty ST 1.1.4 Empty ST 1.1.5 PG 1.1.3 PG 1.1.5 PG 1.1.6 1.1 End Initial   Model 42 coalesce   joinst1 t2 t3 use   inclusive   gateway use   implicit gateway t4 coalesce   splits 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA)
  • 43. tiple 1.1 Start Empty ST 1.1.1 PG 1.1.1 PG 1.1.2 PG 1.1.4 Empty ST 1.1.2 Empty ST 1.1.3 Empty ST 1.1.4 Empty ST 1.1.5 PG 1.1.3 PG 1.1.5 PG 1.1.6 1.1 End Initial   Model 43 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) R1_Parallel_Coalesce_Joins R1.PG Start Empty ST R1.PG.1 PG R1.PG.1 PG R1.PG.2 PG R1.PG.3 Empty ST R1.PG.2 Empty ST R1.PG.3 Empty ST R1.PG.4 Empty ST R1.PG.5 PG R1.PG.4 R1.PG End t1 coalesce   joins
  • 44. 44 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) R2_Parallel_Coalesce_Splits R2.PG Start Empty ST R2.PG.1 PG R2.PG.1 Empty ST R2.PG.2 Empty ST R2.PG.3 Empty ST R2.PG.4 Empty ST R2.PG.5 PG R2.PG.2 PG R2.PG.3 PG 1.1.6 R2.PG End tiple 1.1 Start Empty ST 1.1.1 PG 1.1.1 PG 1.1.2 PG 1.1.4 Empty ST 1.1.2 Empty ST 1.1.3 Empty ST 1.1.4 Empty ST 1.1.5 PG 1.1.3 PG 1.1.5 PG 1.1.6 1.1 End Initial   Model t2 coalesce   splits
  • 45. 45 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) R3_Parallel_Alternative R3.PG Start Empty ST R3.PG.1 Empty ST R3.PG.2 Empty ST R3.PG.3 Empty ST R3.PG.4 Empty ST R3.PG.5 R3.PG EndIG R3.PG.1 IG R3.PG.2 IG R3.PG.4 IG R3.PG.3 IG R3.PG.5 IG R3.PG.6 tiple 1.1 Start Empty ST 1.1.1 PG 1.1.1 PG 1.1.2 PG 1.1.4 Empty ST 1.1.2 Empty ST 1.1.3 Empty ST 1.1.4 Empty ST 1.1.5 PG 1.1.3 PG 1.1.5 PG 1.1.6 1.1 End Initial   Model t3 use   inclusive   gateway
  • 46. 46 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) tiple 1.1 Start Empty ST 1.1.1 PG 1.1.1 PG 1.1.2 PG 1.1.4 Empty ST 1.1.2 Empty ST 1.1.3 Empty ST 1.1.4 Empty ST 1.1.5 PG 1.1.3 PG 1.1.5 PG 1.1.6 1.1 End Initial   Model t4 use   implicit gateway R4_Parallel_Activity_Form R4.PG Start Empty ST R4.PG.1 PG R4.PG.1 PG R4.PG.3 Empty ST R4.PG.2 Empty ST R4.PG.3 Empty ST R4.PG.4 Empty ST R4.PG.5 PG R4.PG.2 PG R4.PG.4 PG R4.PG.5 R4.PG End
  • 47. use   implicit gateway t3 use   inclusive   gateway coalesce   joins 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) t4 1.1.Parallel_Multiple 1.1 Start Empty ST 1.1.1 PG 1.1.1 PG 1.1.2 PG 1.1.4 Empty ST 1.1.2 Empty ST 1.1.3 Empty ST 1.1.4 Empty ST 1.1.5 PG 1.1.3 PG 1.1.5 PG 1.1.6 1.1 End R1_Parallel_Coalesce_Joins R1.PG Start Empty ST R1.PG.1 PG R1.PG.1 PG R1.PG.2 PG R1.PG.3 Empty ST R1.PG.2 Empty ST R1.PG.3 Empty ST R1.PG.4 Empty ST R1.PG.5 PG R1.PG.4 R1.PG End t1 Initial   Model R2_Parallel_Coalesce_Splits R2.PG Start Empty ST R2.PG.1 PG R2.PG.1 Empty ST R2.PG.2 Empty ST R2.PG.3 Empty ST R2.PG.4 Empty ST R2.PG.5 PG R2.PG.2 PG R2.PG.3 PG 1.1.6 R2.PG End t2 coalesce   splits R3_Parallel_Alternative R3.PG Start Empty ST R3.PG.1 Empty ST R3.PG.2 Empty ST R3.PG.3 Empty ST R3.PG.4 Empty ST R3.PG.5 R3.PG EndIG R3.PG.1 IG R3.PG.2 IG R3.PG.4 IG R3.PG.3 IG R3.PG.5 IG R3.PG.6 ctivity_Form R4.PG Start Empty ST R4.PG.1 PG R4.PG.1 PG R4.PG.3 Empty ST R4.PG.2 Empty ST R4.PG.3 Empty ST R4.PG.4 Empty ST R4.PG.5 PG R4.PG.2 PG R4.PG.4 PG R4.PG.5 R4.PG End 47
  • 48. use   implicit gateway t3 use   inclusive   gateway 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) t4 1.1.Parallel_Multiple 1.1 Start Empty ST 1.1.1 PG 1.1.1 PG 1.1.2 PG 1.1.4 Empty ST 1.1.2 Empty ST 1.1.3 Empty ST 1.1.4 Empty ST 1.1.5 PG 1.1.3 PG 1.1.5 PG 1.1.6 1.1 End R1_Parallel_Coalesce_Joins R1.PG Start Empty ST R1.PG.1 PG R1.PG.1 PG R1.PG.2 PG R1.PG.3 Empty ST R1.PG.2 Empty ST R1.PG.3 Empty ST R1.PG.4 Empty ST R1.PG.5 PG R1.PG.4 R1.PG End t1 Initial   Model R2_Parallel_Coalesce_Splits R2.PG Start Empty ST R2.PG.1 PG R2.PG.1 Empty ST R2.PG.2 Empty ST R2.PG.3 Empty ST R2.PG.4 Empty ST R2.PG.5 PG R2.PG.2 PG R2.PG.3 PG 1.1.6 R2.PG End t2 coalesce   splits R3_Parallel_Alternative R3.PG Start Empty ST R3.PG.1 Empty ST R3.PG.2 Empty ST R3.PG.3 Empty ST R3.PG.4 Empty ST R3.PG.5 R3.PG EndIG R3.PG.1 IG R3.PG.2 IG R3.PG.4 IG R3.PG.3 IG R3.PG.5 IG R3.PG.6 ctivity_Form R4.PG Start Empty ST R4.PG.1 PG R4.PG.1 PG R4.PG.3 Empty ST R4.PG.2 Empty ST R4.PG.3 Empty ST R4.PG.4 Empty ST R4.PG.5 PG R4.PG.2 PG R4.PG.4 PG R4.PG.5 R4.PG End 48 coalesce   joins
  • 49. use   implicit gateway t3 use   inclusive   gateway t4 1.1.Parallel_Multiple 1.1 Start Empty ST 1.1.1 PG 1.1.1 PG 1.1.2 PG 1.1.4 Empty ST 1.1.2 Empty ST 1.1.3 Empty ST 1.1.4 Empty ST 1.1.5 PG 1.1.3 PG 1.1.5 PG 1.1.6 1.1 End R1_Parallel_Coalesce_Joins R1.PG Start Empty ST R1.PG.1 PG R1.PG.1 PG R1.PG.2 PG R1.PG.3 Empty ST R1.PG.2 Empty ST R1.PG.3 Empty ST R1.PG.4 Empty ST R1.PG.5 PG R1.PG.4 R1.PG End t1 Initial   Model R2_Parallel_Coalesce_Splits R2.PG Start Empty ST R2.PG.1 PG R2.PG.1 Empty ST R2.PG.2 Empty ST R2.PG.3 Empty ST R2.PG.4 Empty ST R2.PG.5 PG R2.PG.2 PG R2.PG.3 PG 1.1.6 R2.PG End t2 coalesce   splits R3_Parallel_Alternative R3.PG Start Empty ST R3.PG.1 Empty ST R3.PG.2 Empty ST R3.PG.3 Empty ST R3.PG.4 Empty ST R3.PG.5 R3.PG EndIG R3.PG.1 IG R3.PG.2 IG R3.PG.4 IG R3.PG.3 IG R3.PG.5 IG R3.PG.6 ctivity_Form R4.PG Start Empty ST R4.PG.1 PG R4.PG.1 PG R4.PG.3 Empty ST R4.PG.2 Empty ST R4.PG.3 Empty ST R4.PG.4 Empty ST R4.PG.5 PG R4.PG.2 PG R4.PG.4 PG R4.PG.5 R4.PG End 49 coalesce   joins 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA)
  • 50. R3R4 1.2.8 Start Empty ST 1.2.8.1 Empty ST 1.2.8.2 Empty ST 1.2.8.3 Empty ST 1.2.8.4 Empty ST 1.2.8.5 1.2.8 End IG 1.2.8.2 IG 1.2.8.4 IG 1.2.8.5 IG 1.2.8.1 IG 1.2.8.3 use   implicit gateway t3 use   inclusive   gateway 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) t4 1.1.Parallel_Multiple 1.1 Start Empty ST 1.1.1 PG 1.1.1 PG 1.1.2 PG 1.1.4 Empty ST 1.1.2 Empty ST 1.1.3 Empty ST 1.1.4 Empty ST 1.1.5 PG 1.1.3 PG 1.1.5 PG 1.1.6 1.1 End R1_Parallel_Coalesce_Joins R1.PG Start Empty ST R1.PG.1 PG R1.PG.1 PG R1.PG.2 PG R1.PG.3 Empty ST R1.PG.2 Empty ST R1.PG.3 Empty ST R1.PG.4 Empty ST R1.PG.5 PG R1.PG.4 R1.PG End t1 Initial   Model R2_Parallel_Coalesce_Splits R2.PG Start Empty ST R2.PG.1 PG R2.PG.1 Empty ST R2.PG.2 Empty ST R2.PG.3 Empty ST R2.PG.4 Empty ST R2.PG.5 PG R2.PG.2 PG R2.PG.3 PG 1.1.6 R2.PG End t2 coalesce   splits R3_Parallel_Alternative R3.PG Start Empty ST R3.PG.1 Empty ST R3.PG.2 Empty ST R3.PG.3 Empty ST R3.PG.4 Empty ST R3.PG.5 R3.PG EndIG R3.PG.1 IG R3.PG.2 IG R3.PG.4 IG R3.PG.3 IG R3.PG.5 IG R3.PG.6 ctivity_Form R4.PG Start Empty ST R4.PG.1 PG R4.PG.1 PG R4.PG.3 Empty ST R4.PG.2 Empty ST R4.PG.3 Empty ST R4.PG.4 Empty ST R4.PG.5 PG R4.PG.2 PG R4.PG.4 PG R4.PG.5 R4.PG End 1.2.1 Parallel_R1R2 1.2.1 Start Empty ST 1.2.1.1 PG 1.2.1.1 Empty ST 1.2.1.2 Empty ST 1.2.1.5 Empty ST 1.2.1.4 Empty ST 1.2.1.3 PG 1.2.1.2 1.2.1 End R4 1.2.3 Start Empty ST 1.2.3.1 PG 1.2.3.1 PG 1.2.3.2 Empty ST 1.2.3.2 Empty ST 1.2.3.3 Empty ST 1.2.3.4 Empty ST 1.2.3.5 PG 1.2.3.3 1.2.3 End 1.2.5 Parallel_R2R3 1.2.5 Start Empty ST 1.2.5.1 Empty ST 1.2.5.2 Empty ST 1.2.5.3 Empty ST 1.2.5.4 Empty ST 1.2.5.5 1.2.5 EndIG 1.2.5.1 IG 1.2.5.2 IG 1.2.5.3 IG 1.2.5.4 50 3. Generate Transformed BP Models Applicable combinations of rules (RA) Semantically equivalent BP models (TMi) coalesce   joins
  • 51. R3R4 1.2.8 Start Empty ST 1.2.8.1 Empty ST 1.2.8.2 Empty ST 1.2.8.3 Empty ST 1.2.8.4 Empty ST 1.2.8.5 1.2.8 End IG 1.2.8.2 IG 1.2.8.4 IG 1.2.8.5 IG 1.2.8.1 IG 1.2.8.3 use   implicit gateway t3 use   inclusive   gateway 2. Determine Applicable Transformati on Rules Transformat ion rules (R) Applicable combinations of rules (RA) t4 1.1.Parallel_Multiple 1.1 Start Empty ST 1.1.1 PG 1.1.1 PG 1.1.2 PG 1.1.4 Empty ST 1.1.2 Empty ST 1.1.3 Empty ST 1.1.4 Empty ST 1.1.5 PG 1.1.3 PG 1.1.5 PG 1.1.6 1.1 End R1_Parallel_Coalesce_Joins R1.PG Start Empty ST R1.PG.1 PG R1.PG.1 PG R1.PG.2 PG R1.PG.3 Empty ST R1.PG.2 Empty ST R1.PG.3 Empty ST R1.PG.4 Empty ST R1.PG.5 PG R1.PG.4 R1.PG End t1 Initial   Model R2_Parallel_Coalesce_Splits R2.PG Start Empty ST R2.PG.1 PG R2.PG.1 Empty ST R2.PG.2 Empty ST R2.PG.3 Empty ST R2.PG.4 Empty ST R2.PG.5 PG R2.PG.2 PG R2.PG.3 PG 1.1.6 R2.PG End t2 coalesce   splits R3_Parallel_Alternative R3.PG Start Empty ST R3.PG.1 Empty ST R3.PG.2 Empty ST R3.PG.3 Empty ST R3.PG.4 Empty ST R3.PG.5 R3.PG EndIG R3.PG.1 IG R3.PG.2 IG R3.PG.4 IG R3.PG.3 IG R3.PG.5 IG R3.PG.6 ctivity_Form R4.PG Start Empty ST R4.PG.1 PG R4.PG.1 PG R4.PG.3 Empty ST R4.PG.2 Empty ST R4.PG.3 Empty ST R4.PG.4 Empty ST R4.PG.5 PG R4.PG.2 PG R4.PG.4 PG R4.PG.5 R4.PG End 1.2.1 Parallel_R1R2 1.2.1 Start Empty ST 1.2.1.1 PG 1.2.1.1 Empty ST 1.2.1.2 Empty ST 1.2.1.5 Empty ST 1.2.1.4 Empty ST 1.2.1.3 PG 1.2.1.2 1.2.1 End R4 1.2.3 Start Empty ST 1.2.3.1 PG 1.2.3.1 PG 1.2.3.2 Empty ST 1.2.3.2 Empty ST 1.2.3.3 Empty ST 1.2.3.4 Empty ST 1.2.3.5 PG 1.2.3.3 1.2.3 End 1.2.5 Parallel_R2R3 1.2.5 Start Empty ST 1.2.5.1 Empty ST 1.2.5.2 Empty ST 1.2.5.3 Empty ST 1.2.5.4 Empty ST 1.2.5.5 1.2.5 EndIG 1.2.5.1 IG 1.2.5.2 IG 1.2.5.3 IG 1.2.5.4 mi t1 t2 t3 t4 t12 t13 t14 t23 t24 t34 t123 t124 t134 t234 t1234 51 3. Generate Transformed BP Models Applicable combinations of rules (RA) Semantically equivalent BP models (TMi) 3. Generate Transformed BP Models Applicable combinations of rules (RA) Semantically equivalent BP models (TMi) coalesce   joins
  • 52. 52 First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 1.2.1 Parallel_R1R2 1.2.1 Start Empty ST 1.2.1.1 PG 1.2.1.1 Empty ST 1.2.1.2 Empty ST 1.2.1.5 Empty ST 1.2.1.4 Empty ST 1.2.1.3 PG 1.2.1.2 1.2.1 End First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 Workload benchflow [ICPE  ’16][BPM  ’15]
  • 53. 53 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 1.2.1 Parallel_R1R2 1.2.1 Start Empty ST 1.2.1.1 PG 1.2.1.1 Empty ST 1.2.1.2 Empty ST 1.2.1.5 Empty ST 1.2.1.4 Empty ST 1.2.1.3 PG 1.2.1.2 1.2.1 End First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 Workload benchflow [ICPE  ’16][BPM  ’15]
  • 54. 54 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics WfMS First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 1.2.1 Parallel_R1R2 1.2.1 Start Empty ST 1.2.1.1 PG 1.2.1.1 Empty ST 1.2.1.2 Empty ST 1.2.1.5 Empty ST 1.2.1.4 Empty ST 1.2.1.3 PG 1.2.1.2 1.2.1 End First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 Workload Load  function benchflow [ICPE  ’16][BPM  ’15]
  • 55. 55 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics WfMS First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 1.2.1 Parallel_R1R2 1.2.1 Start Empty ST 1.2.1.1 PG 1.2.1.1 Empty ST 1.2.1.2 Empty ST 1.2.1.5 Empty ST 1.2.1.4 Empty ST 1.2.1.3 PG 1.2.1.2 1.2.1 End First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 Workload Load  function benchflow [ICPE  ’16][BPM  ’15]
  • 56. 56 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics WfMS First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 1.2.1 Parallel_R1R2 1.2.1 Start Empty ST 1.2.1.1 PG 1.2.1.1 Empty ST 1.2.1.2 Empty ST 1.2.1.5 Empty ST 1.2.1.4 Empty ST 1.2.1.3 PG 1.2.1.2 1.2.1 End First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 Workload Load  function benchflow [ICPE  ’16][BPM  ’15]
  • 57. 57 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics WfMS First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 1.2.1 Parallel_R1R2 1.2.1 Start Empty ST 1.2.1.1 PG 1.2.1.1 Empty ST 1.2.1.2 Empty ST 1.2.1.5 Empty ST 1.2.1.4 Empty ST 1.2.1.3 PG 1.2.1.2 1.2.1 End First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 Workload Load  function Metrics benchflow [ICPE  ’16][BPM  ’15]
  • 58. 58 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics WfMS First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 1.2.1 Parallel_R1R2 1.2.1 Start Empty ST 1.2.1.1 PG 1.2.1.1 Empty ST 1.2.1.2 Empty ST 1.2.1.5 Empty ST 1.2.1.4 Empty ST 1.2.1.3 PG 1.2.1.2 1.2.1 End First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 Workload Load  function Metrics benchflow [ICPE  ’16][BPM  ’15] instance  duration  in   milliseconds  (ms)  
  • 59. 59 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics 0 100 200 300 400 500 Users Time  (min:sec) 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics v 7.5
  • 60. 60 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics Vincenzo  Ferme 0 100 200 300 400 500 Users Time  (min:sec) 0 10 20 30 40 50 Users Time  (min:sec) 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics v 7.5 v 5.21
  • 61. 61 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics 1 second think time Vincenzo  Ferme 0 100 200 300 400 500 Users Time  (min:sec) 0 10 20 30 40 50 Users Time  (min:sec) 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics v 7.5 v 5.21
  • 63. 63 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics 4. Execute the BPs in EM and Measure Performance Load function / WfMS Performance metrics Instance  duration (ms) Parallel mi t124 2.59  ms ± 0.05  ms 2.16  ms ± 0.03  ms Exclusive t3 t124 1.57  ms ± 0.02  ms 1.32  ms ± 0.02  ms Inclusive mi t1234 2.76  ms ± 0.08  ms 1.78  ms ± 0.02  ms Parallel mi t23 26.04  ms ± 0.01  ms 15.62  ms ± 0.12  ms Exclusive mi t124 2.14  ms ± 0.07  ms 1.39  ms ± 0.02  ms Inclusive mi t1234 29.87  ms ± 0.30  ms 9.93  ms ± 0.14  ms
  • 64. 64 5. Test Statistical Significance of Differences Performance metrics Statistical significance of the performance differences *http://www.biochemia-­‐medica.com/content/comparing-­‐groups-­‐statistical-­‐differences-­‐how-­‐choose-­‐right-­‐statistical-­‐test Population One  sample Two  samples Three  or  more   samples Drawn  from   a  normal   distribution? Drawn  from   a  normal   distribution? Drawn  from   a  normal   distribution? One sample t-­‐test Wilcoxon rank  sum test Paired   samples? Equal variance? Paired t-­‐test Unaired t-­‐test Welch’s corrected unpaired  test Wilcoxon’s matched pairs  test Mann-­‐Whitney test Paired   samples? Paired   samples? Repeated measures one-­‐way  ANOVA Paired   samples? One-­‐way   ANOVA Friedman test Kruskal-­‐Wallis test Yes Yes Yes Yes Yes Yes Yes Yes No No No No No No No No
  • 65. 65 5. Test Statistical Significance of Differences Performance metrics Statistical significance of the performance differences *http://www.biochemia-­‐medica.com/content/comparing-­‐groups-­‐statistical-­‐differences-­‐how-­‐choose-­‐right-­‐statistical-­‐test mi      t1      t2 t3 t4 t12 t13 t14      t23      t24      t34      t123      t124      t134      t234      t1234 One  sample Two  samples Three  or  more   samples Drawn  from   a  normal   distribution? Drawn  from   a  normal   distribution? Drawn  from   a  normal   distribution? One sample t-­‐test Wilcoxon rank  sum test Paired   samples? Equal variance? Paired t-­‐test Unaired t-­‐test Welch’s corrected unpaired  test Wilcoxon’s matched pairs  test Mann-­‐Whitney test Paired   samples? Paired   samples? Repeated measures one-­‐way  ANOVA Paired   samples? One-­‐way   ANOVA Friedman test Kruskal-­‐Wallis test Yes Yes Yes Yes Yes Yes Yes Yes No No No No No No No No Population
  • 66. 66 5. Test Statistical Significance of Differences Performance metrics Statistical significance of the performance differences *http://www.biochemia-­‐medica.com/content/comparing-­‐groups-­‐statistical-­‐differences-­‐how-­‐choose-­‐right-­‐statistical-­‐test mi      t1      t2 t3 t4 t12 t13 t14      t23      t24      t34      t123      t124      t134      t234      t1234 Population One  sample Two  samples Three  or  more   samples Drawn  from   a  normal   distribution? Drawn  from   a  normal   distribution? Drawn  from   a  normal   distribution? One sample t-­‐test Wilcoxon rank  sum test Paired   samples? Equal variance? Paired t-­‐test Unaired t-­‐test Welch’s corrected unpaired  test Wilcoxon’s matched pairs  test Mann-­‐Whitney test Paired   samples? Paired   samples? Repeated measures one-­‐way  ANOVA Paired   samples? One-­‐way   ANOVA Friedman test Kruskal-­‐Wallis test Yes Yes Yes Yes Yes Yes Yes Yes No No No No No No No No
  • 67. 67 5. Test Statistical Significance of Differences Performance metrics Statistical significance of the performance differences *http://www.biochemia-­‐medica.com/content/comparing-­‐groups-­‐statistical-­‐differences-­‐how-­‐choose-­‐right-­‐statistical-­‐test mi      t1      t2 t3 t4 t12 t13 t14      t23      t24      t34      t123      t124      t134      t234      t1234 Three  or  more   samples Drawn  from   a  normal   distribution? Paired   samples? Paired   samples? Repeated measures one-­‐way  ANOVA One-­‐way   ANOVA Friedman test Kruskal-­‐Wallis test Yes Yes Yes No No No
  • 68. 68 5. Test Statistical Significance of Differences Performance metrics Statistical significance of the performance differences *http://www.biochemia-­‐medica.com/content/comparing-­‐groups-­‐statistical-­‐differences-­‐how-­‐choose-­‐right-­‐statistical-­‐test mi      t1      t2 t3 t4 t12 t13 t14      t23      t24      t34      t123      t124      t134      t234      t1234 Three  or  more   samples Drawn  from   a  normal   distribution? Paired   samples? Paired   samples? Repeated measures one-­‐way  ANOVA One-­‐way   ANOVA Friedman test Kruskal-­‐Wallis test Yes Yes Yes No No No
  • 69. 69 5. Test Statistical Significance of Differences Performance metrics Statistical significance of the performance differences *http://www.biochemia-­‐medica.com/content/comparing-­‐groups-­‐statistical-­‐differences-­‐how-­‐choose-­‐right-­‐statistical-­‐test mi      t1      t2 t3 t4 t12 t13 t14      t23      t24      t34      t123      t124      t134      t234      t1234 Three  or  more   samples Drawn  from   a  normal   distribution? Paired   samples? Paired   samples? Repeated measures one-­‐way  ANOVA One-­‐way   ANOVA Friedman test Kruskal-­‐Wallis test Yes Yes Yes No No No
  • 70. 70 5. Test Statistical Significance of Differences Performance metrics Statistical significance of the performance differences RQ1:  Does  the  application  of  different  modeling  practices  have  significant  impact  on  the   duration of  a  BP  instance  execution?  
  • 71. 71 5. Test Statistical Significance of Differences Performance metrics Statistical significance of the performance differences RQ1:  Does  the  application  of  different  modeling  practices  have  significant  impact  on  the   duration of  a  BP  instance  execution?  
  • 72. 72 5. Test Statistical Significance of Differences Performance metrics Statistical significance of the performance differences RQ1:  Does  the  application  of  different  modeling  practices  have  significant  impact  on  the   duration of  a  BP  instance  execution?   YES!
  • 73. 73 5. Test Statistical Significance of Differences Performance metrics Statistical significance of the performance differences RQ1:  Does  the  application  of  different  modeling  practices  have  significant  impact  on  the   duration of  a  BP  instance  execution?   YES! improvement  possibilities  to  BPMS  vendors
  • 74. 74 6. Rank the Performance of Transformed Models Statistical significance of the performance differences RQ2:  Is  there  a  total  order between  semantically  equivalent  but  structurally  different   models,  when  ranked  according  to  their  performance?  
  • 75. 75 6. Rank the Performance of Transformed Models Statistical significance of the performance differences RQ2:  Is  there  a  total  order between  semantically  equivalent  but  structurally  different   models,  when  ranked  according  to  their  performance?   NO!
  • 76. 76 6. Rank the Performance of Transformed Models Statistical significance of the performance differences RQ2:  Is  there  a  total  order between  semantically  equivalent  but  structurally  different   models,  when  ranked  according  to  their  performance?   NO! opportunity  to  identify  optimization  rules  
  • 77. 78 6. Rank the Performance of Transformed Models Statistical significance of the performance differences RQ2:  Is  there  a  total  order between  semantically  equivalent  but  structurally  different   models,  when  ranked  according  to  their  performance?   NO! opportunity  to  identify  optimization  rules  
  • 78. 78 6. Rank the Performance of Transformed Models Statistical significance of the performance differences RQ2:  Is  there  a  total  order between  semantically  equivalent  but  structurally  different   models,  when  ranked  according  to  their  performance?   NO! opportunity  to  identify  optimization  rules  
  • 79. 79 Performance  Variability Acceptability  index 𝑨𝑰 𝑨, 𝑩 =   𝒎 𝑩 − 𝒎(𝑨) 𝒘 𝑩 + 𝒘(𝑨) *Sengupta,  A.,  Pal,  T.K.:  On  comparing  interval  numbers.  European  Journal  of  Operational  Research  127(1),  28–43  (2000)   𝐴 = [𝑎𝑙, 𝑎𝑟] 𝐵 = [𝑏𝑙, 𝑏𝑟] 95%  confidence  interval of  the  duration 𝑚 𝐴 𝑚 𝐵 average  duration  of model’s  instances w 𝐴 w 𝐵 half-­‐width  of  the confidence  interval 𝐴 𝐵 initial  model  (mi) transformed  model  (t)
  • 80. 80 Performance  Variability Acceptability  index 𝑨𝑰 𝑨, 𝑩 =   𝒎 𝑩 − 𝒎(𝑨) 𝒘 𝑩 + 𝒘(𝑨) *Sengupta,  A.,  Pal,  T.K.:  On  comparing  interval  numbers.  European  Journal  of  Operational  Research  127(1),  28–43  (2000)   𝐴 = [𝑎𝑙, 𝑎𝑟] 𝐵 = [𝑏𝑙, 𝑏𝑟] 95%  confidence  interval of  the  duration 𝑚 𝐴 𝑚 𝐵 average  duration  of model’s  instances w 𝐴 w 𝐵 half-­‐width  of  the confidence  interval 𝐴 𝐵 initial  model  (mi) transformed  model  (t) -­‐1 1𝐴𝐼 overlapping intervals
  • 81. 81 Performance  Variability Acceptability  index 𝑨𝑰 𝑨, 𝑩 =   𝒎 𝑩 − 𝒎(𝑨) 𝒘 𝑩 + 𝒘(𝑨) *Sengupta,  A.,  Pal,  T.K.:  On  comparing  interval  numbers.  European  Journal  of  Operational  Research  127(1),  28–43  (2000)   𝐴 = [𝑎𝑙, 𝑎𝑟] 𝐵 = [𝑏𝑙, 𝑏𝑟] 95%  confidence  interval of  the  duration 𝑚 𝐴 𝑚 𝐵 average  duration  of model’s  instances w 𝐴 w 𝐵 half-­‐width  of  the confidence  interval 𝐴 𝐵 initial  model  (mi) transformed  model  (t) -­‐1 1𝐴𝐼 transformed  model is  faster overlapping intervals
  • 82. 82 Performance  Variability Acceptability  index 𝑨𝑰 𝑨, 𝑩 =   𝒎 𝑩 − 𝒎(𝑨) 𝒘 𝑩 + 𝒘(𝑨) *Sengupta,  A.,  Pal,  T.K.:  On  comparing  interval  numbers.  European  Journal  of  Operational  Research  127(1),  28–43  (2000)   𝐴 = [𝑎𝑙, 𝑎𝑟] 𝐵 = [𝑏𝑙, 𝑏𝑟] 95%  confidence  interval of  the  duration 𝑚 𝐴 𝑚 𝐵 average  duration  of model’s  instances w 𝐴 w 𝐵 half-­‐width  of  the confidence  interval 𝐴 𝐵 initial  model  (mi) transformed  model  (t) -­‐1 1𝐴𝐼 initial  model is  faster transformed  model is  faster overlapping intervals
  • 83. 11.# 12.# 8.# 13.# 9.# 5.# 10.# 2.# 12.# 7.# 3.# 9.# 6.# 4.# 1.# 7.# 7.# 12.# 8.# 3.# 9.# 4.# 8.# 5.# 10.# 3.# 1.# 6.# 6.# 2.# !32$ !30$ !28$ !26$ !24$ !22$ !20$ !18$ !16$ !14$ !12$ !10$ !8$ !6$ !4$ !2$ 0$ 2$ t1$ t2$ t3$ t4$ t12$ t13$ t14$ t23$ t24$ t34$ t123$ t124$ t134$ t234$ t1234$ Acceptability#Index# Parallel#Control#Flow#(EX1_PCF)# Trial$1$!$Ac2vi2$ Trial$2$!$Ac2vi2$ Trial$3$!$Ac2vi2$ Trial$1$!$Camunda$ Trial$2$!$Camunda$ Trial$3$!$Camunda$ Ac2vi2$Ranks$1.#to#14.# Camunda$Ranks$1.#to#12.# Overlapping$$ confidence$intervals$ 83 Performance  Variability
  • 84. 11.# 12.# 8.# 13.# 9.# 5.# 10.# 2.# 12.# 7.# 3.# 9.# 6.# 4.# 1.# 7.# 7.# 12.# 8.# 3.# 9.# 4.# 8.# 5.# 10.# 3.# 1.# 6.# 6.# 2.# !32$ !30$ !28$ !26$ !24$ !22$ !20$ !18$ !16$ !14$ !12$ !10$ !8$ !6$ !4$ !2$ 0$ 2$ t1$ t2$ t3$ t4$ t12$ t13$ t14$ t23$ t24$ t34$ t123$ t124$ t134$ t234$ t1234$ Acceptability#Index# Parallel#Control#Flow#(EX1_PCF)# Trial$1$!$Ac2vi2$ Trial$2$!$Ac2vi2$ Trial$3$!$Ac2vi2$ Trial$1$!$Camunda$ Trial$2$!$Camunda$ Trial$3$!$Camunda$ Ac2vi2$Ranks$1.#to#14.# Camunda$Ranks$1.#to#12.# Overlapping$$ confidence$intervals$ 84 Performance  Variability
  • 85. 11.# 12.# 8.# 13.# 9.# 5.# 10.# 2.# 12.# 7.# 3.# 9.# 6.# 4.# 1.# 7.# 7.# 12.# 8.# 3.# 9.# 4.# 8.# 5.# 10.# 3.# 1.# 6.# 6.# 2.# !32$ !30$ !28$ !26$ !24$ !22$ !20$ !18$ !16$ !14$ !12$ !10$ !8$ !6$ !4$ !2$ 0$ 2$ t1$ t2$ t3$ t4$ t12$ t13$ t14$ t23$ t24$ t34$ t123$ t124$ t134$ t234$ t1234$ Acceptability#Index# Parallel#Control#Flow#(EX1_PCF)# Trial$1$!$Ac2vi2$ Trial$2$!$Ac2vi2$ Trial$3$!$Ac2vi2$ Trial$1$!$Camunda$ Trial$2$!$Camunda$ Trial$3$!$Camunda$ Ac2vi2$Ranks$1.#to#14.# Camunda$Ranks$1.#to#12.# Overlapping$$ confidence$intervals$ 85 Performance  Variability
  • 86. 11.# 12.# 8.# 13.# 9.# 5.# 10.# 2.# 12.# 7.# 3.# 9.# 6.# 4.# 1.# 7.# 7.# 12.# 8.# 3.# 9.# 4.# 8.# 5.# 10.# 3.# 1.# 6.# 6.# 2.# !32$ !30$ !28$ !26$ !24$ !22$ !20$ !18$ !16$ !14$ !12$ !10$ !8$ !6$ !4$ !2$ 0$ 2$ t1$ t2$ t3$ t4$ t12$ t13$ t14$ t23$ t24$ t34$ t123$ t124$ t134$ t234$ t1234$ Acceptability#Index# Parallel#Control#Flow#(EX1_PCF)# Trial$1$!$Ac2vi2$ Trial$2$!$Ac2vi2$ Trial$3$!$Ac2vi2$ Trial$1$!$Camunda$ Trial$2$!$Camunda$ Trial$3$!$Camunda$ Ac2vi2$Ranks$1.#to#14.# Camunda$Ranks$1.#to#12.# Overlapping$$ confidence$intervals$ 86 1.3.5 Parallel_R1R2R3R4 1.3.5 Start Empty ST 1.3.5.1 Empty ST 1.3.5.2 Empty ST 1.3.5.3 Empty ST 1.3.5.4 Empty ST 1.3.5.5 1.3.5 End IG 1.3.5.1 t1234 Performance  Variability
  • 87. 11.# 12.# 8.# 13.# 9.# 5.# 10.# 2.# 12.# 7.# 3.# 9.# 6.# 4.# 1.# 7.# 7.# 12.# 8.# 3.# 9.# 4.# 8.# 5.# 10.# 3.# 1.# 6.# 6.# 2.# !32$ !30$ !28$ !26$ !24$ !22$ !20$ !18$ !16$ !14$ !12$ !10$ !8$ !6$ !4$ !2$ 0$ 2$ t1$ t2$ t3$ t4$ t12$ t13$ t14$ t23$ t24$ t34$ t123$ t124$ t134$ t234$ t1234$ Acceptability#Index# Parallel#Control#Flow#(EX1_PCF)# Trial$1$!$Ac2vi2$ Trial$2$!$Ac2vi2$ Trial$3$!$Ac2vi2$ Trial$1$!$Camunda$ Trial$2$!$Camunda$ Trial$3$!$Camunda$ Ac2vi2$Ranks$1.#to#14.# Camunda$Ranks$1.#to#12.# Overlapping$$ confidence$intervals$ 87 1.3.5 Parallel_R1R2R3R4 1.3.5 Start Empty ST 1.3.5.1 Empty ST 1.3.5.2 Empty ST 1.3.5.3 Empty ST 1.3.5.4 Empty ST 1.3.5.5 1.3.5 End IG 1.3.5.1 t1234 1.3.2 Parallel_R1R2R4 1.3.2 Start Empty ST 1.3.2.1 Empty ST 1.3.2.2 Empty ST 1.3.2.3 Empty ST 1.3.2.4 Empty ST 1.3.2.5 PG 1.3.2.1 1.3.2 End t124 Performance  Variability
  • 88. Performance Variability 5.# 5.# 6.# 5.# 3.# 5.# 3.# 5.# 2.# 5.# 4.# 1.# 4.# 4.# 2.# 4.# 5.# 7.# 6.# 2.# 4.# 3.# 5.# 2.# 5.# 2.# 1.# 3.# 2.# 1.# !8# !7# !6# !5# !4# !3# !2# !1# 0# 1# 2# t1# t2# t3# t4# t12# t13# t14# t23# t24# t34# t123# t124# t134# t234# t1234# Acceptability#Index# Exclusive#Control#Flow#(EX2_ECF)# Trial#1#!#Ac4vi4# Trial#2#!#Ac4vi4# Trial#3#!#Ac4vi4# Trial#1#!#Camunda# Trial#2#!#Camunda# Trial#3#!#Camunda# Ac4vi4#Ranks#1.#to#6.# Camunda#Ranks#1.#to#7.# Overlapping## confidence#intervals# 88
  • 89. Performance Variability 5.# 5.# 6.# 5.# 3.# 5.# 3.# 5.# 2.# 5.# 4.# 1.# 4.# 4.# 2.# 4.# 5.# 7.# 6.# 2.# 4.# 3.# 5.# 2.# 5.# 2.# 1.# 3.# 2.# 1.# !8# !7# !6# !5# !4# !3# !2# !1# 0# 1# 2# t1# t2# t3# t4# t12# t13# t14# t23# t24# t34# t123# t124# t134# t234# t1234# Acceptability#Index# Exclusive#Control#Flow#(EX2_ECF)# Trial#1#!#Ac4vi4# Trial#2#!#Ac4vi4# Trial#3#!#Ac4vi4# Trial#1#!#Camunda# Trial#2#!#Camunda# Trial#3#!#Camunda# Ac4vi4#Ranks#1.#to#6.# Camunda#Ranks#1.#to#7.# Overlapping## confidence#intervals# 89 3.3.2 Exclusive_R1R2R4 3.3.2 Start Empty ST 3.3.2.2 Empty ST 3.3.2.5 EG 3.3.2.1 Empty ST 3.3.2.6 3.3.2 End Empty ST 3.3.2.3 Empty ST 3.3.2.4 Generate ST 3.3.2.1 a==3a==0 a == 1 a == 2 t124
  • 90. Performance Variability 5.# 5.# 6.# 5.# 3.# 5.# 3.# 5.# 2.# 5.# 4.# 1.# 4.# 4.# 2.# 4.# 5.# 7.# 6.# 2.# 4.# 3.# 5.# 2.# 5.# 2.# 1.# 3.# 2.# 1.# !8# !7# !6# !5# !4# !3# !2# !1# 0# 1# 2# t1# t2# t3# t4# t12# t13# t14# t23# t24# t34# t123# t124# t134# t234# t1234# Acceptability#Index# Exclusive#Control#Flow#(EX2_ECF)# Trial#1#!#Ac4vi4# Trial#2#!#Ac4vi4# Trial#3#!#Ac4vi4# Trial#1#!#Camunda# Trial#2#!#Camunda# Trial#3#!#Camunda# Ac4vi4#Ranks#1.#to#6.# Camunda#Ranks#1.#to#7.# Overlapping## confidence#intervals# 90 3.3.3 Exclusive_R1R3R4 3.3.3 Start Empty ST 3.3.3.2 Empty ST 3.3.3.5 Empty ST 3.3.3.6 3.3.3 End Empty ST 3.3.3.3 Empty ST 3.3.3.4 Generate ST 3.3.3.1 IG 3.3.3.1 IG 3.3.3.2 IG 3.3.3.3 a==1a==2a==3a==0 a == 0 || a == 1 a == 2 || a == 3 3.3.2 Exclusive_R1R2R4 3.3.2 Start Empty ST 3.3.2.2 Empty ST 3.3.2.5 EG 3.3.2.1 Empty ST 3.3.2.6 3.3.2 End Empty ST 3.3.2.3 Empty ST 3.3.2.4 Generate ST 3.3.2.1 a==3a==0 a == 1 a == 2 t124 t1234
  • 91. Performance  Variability 9.# 10.# 4.# 11.# 6.# 3.# 7.# 2.# 8.# 3.# 1.# 5.# 3.# 2.# 1.# 9.# 10.# 6.# 11.# 8.# 4.# 9.# 4.# 9.# 5.# 2.# 7.# 3.# 3.# 1.# !50$ !48$ !46$ !44$ !42$ !40$ !38$ !36$ !34$ !32$ !30$ !28$ !26$ !24$ !22$ !20$ !18$ !16$ !14$ !12$ !10$ !8$ !6$ !4$ !2$ 0$ 2$ t1$ t2$ t3$ t4$ t12$ t13$ t14$ t23$ t24$ t34$ t123$ t124$ t134$ t234$ t1234$ Acceptability#Index# Inclusive#Control#Flow#(EX3_ICF)# Trial$1$!$Ac3vi3$ Trial$2$!$Ac3vi3$ Trial$3$!$Ac3vi3$ Trial$1$!$Camunda$ Trial$2$!$Camunda$ Trial$3$!$Camunda$ Ac3vi3$Ranks$1.#to#11.# Camunda$Ranks$1.#to#12.# Overlapping$$ confidence$intervals$ 91
  • 92. Performance  Variability 9.# 10.# 4.# 11.# 6.# 3.# 7.# 2.# 8.# 3.# 1.# 5.# 3.# 2.# 1.# 9.# 10.# 6.# 11.# 8.# 4.# 9.# 4.# 9.# 5.# 2.# 7.# 3.# 3.# 1.# !50$ !48$ !46$ !44$ !42$ !40$ !38$ !36$ !34$ !32$ !30$ !28$ !26$ !24$ !22$ !20$ !18$ !16$ !14$ !12$ !10$ !8$ !6$ !4$ !2$ 0$ 2$ t1$ t2$ t3$ t4$ t12$ t13$ t14$ t23$ t24$ t34$ t123$ t124$ t134$ t234$ t1234$ Acceptability#Index# Inclusive#Control#Flow#(EX3_ICF)# Trial$1$!$Ac3vi3$ Trial$2$!$Ac3vi3$ Trial$3$!$Ac3vi3$ Trial$1$!$Camunda$ Trial$2$!$Camunda$ Trial$3$!$Camunda$ Ac3vi3$Ranks$1.#to#11.# Camunda$Ranks$1.#to#12.# Overlapping$$ confidence$intervals$ 92
  • 93. Performance  Variability 9.# 10.# 4.# 11.# 6.# 3.# 7.# 2.# 8.# 3.# 1.# 5.# 3.# 2.# 1.# 9.# 10.# 6.# 11.# 8.# 4.# 9.# 4.# 9.# 5.# 2.# 7.# 3.# 3.# 1.# !50$ !48$ !46$ !44$ !42$ !40$ !38$ !36$ !34$ !32$ !30$ !28$ !26$ !24$ !22$ !20$ !18$ !16$ !14$ !12$ !10$ !8$ !6$ !4$ !2$ 0$ 2$ t1$ t2$ t3$ t4$ t12$ t13$ t14$ t23$ t24$ t34$ t123$ t124$ t134$ t234$ t1234$ Acceptability#Index# Inclusive#Control#Flow#(EX3_ICF)# Trial$1$!$Ac3vi3$ Trial$2$!$Ac3vi3$ Trial$3$!$Ac3vi3$ Trial$1$!$Camunda$ Trial$2$!$Camunda$ Trial$3$!$Camunda$ Ac3vi3$Ranks$1.#to#11.# Camunda$Ranks$1.#to#12.# Overlapping$$ confidence$intervals$ 93
  • 94. Performance  Variability 9.# 10.# 4.# 11.# 6.# 3.# 7.# 2.# 8.# 3.# 1.# 5.# 3.# 2.# 1.# 9.# 10.# 6.# 11.# 8.# 4.# 9.# 4.# 9.# 5.# 2.# 7.# 3.# 3.# 1.# !50$ !48$ !46$ !44$ !42$ !40$ !38$ !36$ !34$ !32$ !30$ !28$ !26$ !24$ !22$ !20$ !18$ !16$ !14$ !12$ !10$ !8$ !6$ !4$ !2$ 0$ 2$ t1$ t2$ t3$ t4$ t12$ t13$ t14$ t23$ t24$ t34$ t123$ t124$ t134$ t234$ t1234$ Acceptability#Index# Inclusive#Control#Flow#(EX3_ICF)# Trial$1$!$Ac3vi3$ Trial$2$!$Ac3vi3$ Trial$3$!$Ac3vi3$ Trial$1$!$Camunda$ Trial$2$!$Camunda$ Trial$3$!$Camunda$ Ac3vi3$Ranks$1.#to#11.# Camunda$Ranks$1.#to#12.# Overlapping$$ confidence$intervals$ 94
  • 95. Performance  Variability 9.# 10.# 4.# 11.# 6.# 3.# 7.# 2.# 8.# 3.# 1.# 5.# 3.# 2.# 1.# 9.# 10.# 6.# 11.# 8.# 4.# 9.# 4.# 9.# 5.# 2.# 7.# 3.# 3.# 1.# !50$ !48$ !46$ !44$ !42$ !40$ !38$ !36$ !34$ !32$ !30$ !28$ !26$ !24$ !22$ !20$ !18$ !16$ !14$ !12$ !10$ !8$ !6$ !4$ !2$ 0$ 2$ t1$ t2$ t3$ t4$ t12$ t13$ t14$ t23$ t24$ t34$ t123$ t124$ t134$ t234$ t1234$ Acceptability#Index# Inclusive#Control#Flow#(EX3_ICF)# Trial$1$!$Ac3vi3$ Trial$2$!$Ac3vi3$ Trial$3$!$Ac3vi3$ Trial$1$!$Camunda$ Trial$2$!$Camunda$ Trial$3$!$Camunda$ Ac3vi3$Ranks$1.#to#11.# Camunda$Ranks$1.#to#12.# Overlapping$$ confidence$intervals$ 95 2.3.2 Inclusive_R1R2R4 (Copy) 2.3.2 Start Empty ST 2.3.2.2 Empty ST 2.3.2.5 2.3.2 End Empty ST 2.3.2.3 Empty ST 2.3.2.4 Generate ST 2.3.2.1 IG 2.3.2.1 a==0 b == 0 d==0 c == 0 t1234
  • 96. Performance  Variability 9.# 10.# 4.# 11.# 6.# 3.# 7.# 2.# 8.# 3.# 1.# 5.# 3.# 2.# 1.# 9.# 10.# 6.# 11.# 8.# 4.# 9.# 4.# 9.# 5.# 2.# 7.# 3.# 3.# 1.# !50$ !48$ !46$ !44$ !42$ !40$ !38$ !36$ !34$ !32$ !30$ !28$ !26$ !24$ !22$ !20$ !18$ !16$ !14$ !12$ !10$ !8$ !6$ !4$ !2$ 0$ 2$ t1$ t2$ t3$ t4$ t12$ t13$ t14$ t23$ t24$ t34$ t123$ t124$ t134$ t234$ t1234$ Acceptability#Index# Inclusive#Control#Flow#(EX3_ICF)# Trial$1$!$Ac3vi3$ Trial$2$!$Ac3vi3$ Trial$3$!$Ac3vi3$ Trial$1$!$Camunda$ Trial$2$!$Camunda$ Trial$3$!$Camunda$ Ac3vi3$Ranks$1.#to#11.# Camunda$Ranks$1.#to#12.# Overlapping$$ confidence$intervals$ 96 2.3.2 Inclusive_R1R2R4 (Copy) 2.3.2 Start Empty ST 2.3.2.2 Empty ST 2.3.2.5 2.3.2 End Empty ST 2.3.2.3 Empty ST 2.3.2.4 Generate ST 2.3.2.1 IG 2.3.2.1 a==0 b == 0 d==0 c == 0 2.2.1 Inclusive_R1R2 (Copy) 2.2.1 Start Empty ST 2.2.1.2 Empty ST 2.2.1.5 2.2.1 End Empty ST 2.2.1.3 Empty ST 2.2.1.4 Generate ST 2.2.1.1 IG 2.2.1.1 IG 2.2.1.2 a==0d==0 b == 0 c == 0 t123 t1234
  • 97. Avoid  Inclusive  Gateways   97 Modeling  practices  and  performance
  • 98. Avoid  Inclusive  Gateways   98 Modeling  practices  and  performance EX3_ICFECF 2.2 2.5 Empty ST 2.6 2 End 2.3 2.4 G 2.3 G 2.5 EG 2.6 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0
  • 99. Avoid  Inclusive  Gateways   99 Modeling  practices  and  performance Use  inclusive  gateways EX3_ICFECF 2.2 2.5 Empty ST 2.6 2 End 2.3 2.4 G 2.3 G 2.5 EG 2.6 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0
  • 100. Avoid  Inclusive  Gateways   100 Modeling  practices  and  performance Use  inclusive  gateways EX3_ICFECF 2.2 2.5 Empty ST 2.6 2 End 2.3 2.4 G 2.3 G 2.5 EG 2.6 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 2.1.Inclusive_Multiple 2.1 Start Empty ST 2.1.2 Empty ST 2.1.5 2.1 End Empty ST 2.1.3 Empty ST 2.1.4 Generate ST 2.1.1 IG 2.1.1 IG 2.1.2 IG 2.1.4 IG 2.1.3 IG 2.1.5 IG 2.1.6 a==0||b==0c==0||d==0 a==0b==0c==0d==0 First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0
  • 101. Avoid  Inclusive  Gateways   101 Modeling  practices  and  performance Use  inclusive  gateways EX3_ICFECF 2.2 2.5 Empty ST 2.6 2 End 2.3 2.4 G 2.3 G 2.5 EG 2.6 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 2.1.Inclusive_Multiple 2.1 Start Empty ST 2.1.2 Empty ST 2.1.5 2.1 End Empty ST 2.1.3 Empty ST 2.1.4 Generate ST 2.1.1 IG 2.1.1 IG 2.1.2 IG 2.1.4 IG 2.1.3 IG 2.1.5 IG 2.1.6 a==0||b==0c==0||d==0 a==0b==0c==0d==0 Camunda 2.76  ms ± 0.08  ms Camunda 2.02  ms ± 0.03  msFirst models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0
  • 102. Avoid  Inclusive  Gateways   102 Modeling  practices  and  performance Use  inclusive  gateways EX3_ICFECF 2.2 2.5 Empty ST 2.6 2 End 2.3 2.4 G 2.3 G 2.5 EG 2.6 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 2.1.Inclusive_Multiple 2.1 Start Empty ST 2.1.2 Empty ST 2.1.5 2.1 End Empty ST 2.1.3 Empty ST 2.1.4 Generate ST 2.1.1 IG 2.1.1 IG 2.1.2 IG 2.1.4 IG 2.1.3 IG 2.1.5 IG 2.1.6 a==0||b==0c==0||d==0 a==0b==0c==0d==0 Camunda 2.76  ms ± 0.08  ms Camunda 2.02  ms ± 0.03  msFirst models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 Activiti   29.87ms  ± 0.30  ms Activiti   11.66  ms ± 0.16  ms
  • 103. Avoid  Inclusive  Gateways   103 Modeling  practices  and  performance Use  inclusive  gateways EX3_ICFECF 2.2 2.5 Empty ST 2.6 2 End 2.3 2.4 G 2.3 G 2.5 EG 2.6 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 2.1.Inclusive_Multiple 2.1 Start Empty ST 2.1.2 Empty ST 2.1.5 2.1 End Empty ST 2.1.3 Empty ST 2.1.4 Generate ST 2.1.1 IG 2.1.1 IG 2.1.2 IG 2.1.4 IG 2.1.3 IG 2.1.5 IG 2.1.6 a==0||b==0c==0||d==0 a==0b==0c==0d==0 Camunda 2.76  ms ± 0.08  ms Camunda 2.02  ms ± 0.03  msFirst models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 R3_Parallel_Alternative R3.PG Start Empty ST R3.PG.1 Empty ST R3.PG.2 Empty ST R3.PG.3 Empty ST R3.PG.4 Empty ST R3.PG.5 R3.PG EndIG R3.PG.1 IG R3.PG.2 IG R3.PG.4 IG R3.PG.3 IG R3.PG.5 IG R3.PG.6 Activiti   29.87ms  ± 0.30  ms Activiti   11.66  ms ± 0.16  ms Activiti   26.04  ms ± 0.21  ms Activiti   19.57  ms ± 0.18  ms
  • 104. Avoid  Inclusive  Gateways   104 Modeling  practices  and  performance Use  inclusive  gateways EX3_ICFECF 2.2 2.5 Empty ST 2.6 2 End 2.3 2.4 G 2.3 G 2.5 EG 2.6 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 2.1.Inclusive_Multiple 2.1 Start Empty ST 2.1.2 Empty ST 2.1.5 2.1 End Empty ST 2.1.3 Empty ST 2.1.4 Generate ST 2.1.1 IG 2.1.1 IG 2.1.2 IG 2.1.4 IG 2.1.3 IG 2.1.5 IG 2.1.6 a==0||b==0c==0||d==0 a==0b==0c==0d==0 Camunda 2.76  ms ± 0.08  ms Camunda 2.02  ms ± 0.03  msFirst models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 Camunda 2.51  ms ± 0.05  ms Camunda 2.58  ms ± 0.05  ms R3_Parallel_Alternative R3.PG Start Empty ST R3.PG.1 Empty ST R3.PG.2 Empty ST R3.PG.3 Empty ST R3.PG.4 Empty ST R3.PG.5 R3.PG EndIG R3.PG.1 IG R3.PG.2 IG R3.PG.4 IG R3.PG.3 IG R3.PG.5 IG R3.PG.6 Activiti   29.87ms  ± 0.30  ms Activiti   11.66  ms ± 0.16  ms Activiti   26.04  ms ± 0.21  ms Activiti   19.57  ms ± 0.18  ms
  • 105. Use  as  Few  Elements  as  Possibile 105 Modeling  practices  and  performance
  • 106. Use  as  Few  Elements  as  Possible 106 Modeling  practices  and  performance
  • 107. Use  as  Few  Elements  as  Possible 107 Modeling  practices  and  performance
  • 108. Use  as  Few  Elements  as  Possible 108 Modeling  practices  and  performance
  • 109. Minimize  the  routing  paths  per  element Model  as  structured  as  possible 109 Modeling  practices  and  performance
  • 110. Minimize  the  routing  paths  per  element Model  as  structured  as  possible 110 1.3.5 Parallel_R1R2R3R4 1.3.5 Start Empty ST 1.3.5.1 Empty ST 1.3.5.2 Empty ST 1.3.5.3 Empty ST 1.3.5.4 Empty ST 1.3.5.5 1.3.5 End IG 1.3.5.1 t124 t1234 Best  performing  models Modeling  practices  and  performance 1.3.2 Start Empty ST 1.3.2.1 Empty ST 1.3.2.2 Empty ST 1.3.2.3 Empty ST 1.3.2.4 Empty ST 1.3.2.5 PG 1.3.2.1 1.3.2 End
  • 111. Conclusions 111 Modeling  is  a  discretional  decision  of  the  modeler!!!
  • 112. Conclusions 112 Our  ultimate  goal:   Take  the  model  and  transform  it  to  a  better  performing  but  semantically   equivalent  model Modeling  is  a  discretional  decision  of  the  modeler!!!
  • 113. Conclusions 113 Our  ultimate  goal:   Take  the  model  and  transform  it  to  a  better  performing  but  semantically   equivalent  model Modeling  is  a  discretional  decision  of  the  modeler!!! Our  challenge:   Define  optimization  rules  to  obtain  the  better  performing  model  
  • 115. Conclusions 115 ~𝟏𝟕% ~𝟏𝟓% ~𝟑𝟔% ~𝟒𝟎% ~𝟑𝟓% ~𝟔𝟕% New  automatic  optimization  opportunity? in  milliseconds in  milliseconds
  • 116. On  the   Performance  Overhead of BPMN  Modeling  Practices   ana.ivanchikj@usi.ch
  • 118. 118 empty  tasks script  task script  task FULLY  AUTOMATED 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) 1. Design the Initial BP Model Modelling guidelines / practices / conventions Initial BP model (mi) First models v4 EX1_PCF EX2_E 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2 Empty ST 2 EG 2.1 Empty ST 2 Empty ST 2 EG 2.2 EG 2.4 EG EG Generate ST 2.1 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 Parallel First models v4 EX1_PCF EX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 3 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 First models v4 EX1_PCF EX3_ICFEX2_ECF 1 Start Empty ST 1.1 PG 1.1 PG 1.2 PG 1.4 Empty ST 1.2 Empty ST 1.3 Empty ST 1.4 Empty ST 1.5 PG 1.3 PG 1.5 PG 1.6 1 End 2 Start Empty ST 2.2 Empty ST 2.5 EG 2.1 Empty ST 2.6 2 End Empty ST 2.3 Empty ST 2.4 EG 2.2 EG 2.4 EG 2.3 EG 2.5 EG 2.6Generate ST 2.1 PG 3.4 EG 3.1 Empty 3.2 EG 3.2 EG 3.3 Empty ST 3.3 EG 3.4 PG 3.3 3 End Generate ST 3.1 3 Start EG 3.5 Empty ST 3.4 EG 3.6 EG 3.7 Empty ST 3.5 EG 3.8 PG 3.1 PG 3.2 PG 3.6 PG 3.5 a==1a==3 a==2||a==3a==0||a==1 a==0a==2 b==0 a == 0 c == 0 b == 1 a==1 c == 1 d == 1 d == 0 Exclusive Inclusive
  • 119. 119 Model  ranking Dunn’s  test  -­‐ the  H0 is  that  the  probability  of  observing  a  randomly  selected  value  from  the   first  sample  that  is  larger  than  a  randomly  selected  value  from  the  second  sample  equals   one  half,  i.e.,  no  sample  dominates  the  other =>  we  assign  the  same  rank. Rejecting  the  H0,  implies  that  the  first  sample  is  dominated  by  the  second  sample =>  we   assign  different  ranks. Base-­‐case  rank  -­‐ the  sum of  the  assigned  ranks  in  each performed  trial (what  we  show  in   the  table). Sensitivity  analysis  -­‐ we  test  the  sensitivity  of  the  order  of  the  performance  of  the  executed   models  as  per  the  base-­‐case  rank  on  the  the  ranks  from  the  individual  trials.  We  use  a   deterministic  one-­‐at-­‐a-­‐time,  also  known  as  one-­‐side,  sensitivity  analysis.
  • 120. 120 -­‐ the  WfMS,  the  DB  and  Faban,  are  all  deployed  in  Docker  images  on  dedicated  servers   using  the  Docker  Engine  1.9.1  and  Ubuntu 14.04.3  LTS  (GNU/Linux  3.13.0-­‐40-­‐generic   x86  64)  as  OS.   -­‐ they  interact  through  two  networks of  10Gbit/s  each,  one  dedicated  to  the   communication  between  the  WfMS and  the  DB  and  the  other  one  dedicated  to  other   interactions  (e.g.,  issuing  the  load).   -­‐ The  WfMS runs  on  a  server with  64  Cores  (2  threads)  and  a  clock  speed  of  1’400MHz   mounting  128GB  of  RAM  and  a  magnetic  disk  with  15’000  rpm.   -­‐ The  DB runs  on  a  server with  64  Cores  (2  threads)  and  a  clock  speed  of  2’300MHz   mounting  128GB  of  RAM  and  a  SSD  SATA  disk.   -­‐ Faban’s Load  Drivers  are  placed  on  three  servers:  one  with  64  Cores  (2  threads)  and  a   clock  speed  of  2’300MHz  mounting  128GB  of  RAM,  the  second  with  48  Cores  (2   threads)  and  a  clock  speed  of  2’000MHz  mounting  128GB  of  RAM,  and  the  third  with   12  Cores  (1  thread)  at  800MHz  mounting  64GB  of  RAM.   Benchflow Environment  Setup