Petri Net

The Application of Petri Nets
to Workflow Management
W.M.P. van der Aalst
Department of Mathematics and Computing Science, Eindhoven University of Technology,
P.O. Box 513, NL-5600 MB, Eindhoven, The Netherlands, telephone: -31 40 2474295,
e-mail: wsinwa@win.tue.nl

Abstract
Workflow management promises a new solution to an age-old problem: control-
ling, monitoring, optimizing and supporting business processes. What is new about
workflow management is the explicit representation of the business process logic
which allows for computerized support. This paper discusses the use of Petri nets
in the context of workflow management. Petri nets are an established tool for mod-
eling and analyzing processes. On the one hand, Petri nets can be used as a design
language for the specification of complex workflows. On the other hand, Petri net
theory provides for powerful analysis techniques which can be used to verify the
correctness of workflow procedures. This paper introduces workflow management
as an application domain for Petri nets, presents state-of-the-art results with re-
spect to the verification of workflows, and highlights some Petri-net-based work-
flow tools.

1 Introduction
In former times, information systems were designed to support the execution of
individual tasks. Today’s information systems need to support the business pro-
cesses at hand. It no longer suffices to focus on just the tasks. The information
system also needs to control, monitor and support the logistical aspects of a busi-
ness process. In other words, the information system also has to manage the flow
of work through the organization. Many organizations with complex business pro-
cesses have identified the need for concepts, techniques, and tools to support the
management of workflows. Based on this need the term workflow management
was born (cf. [HL91, Kou95]).
Until recently there were no generic tools to support workflow management. As a
result, parts of the business process were hard-coded in the applications. For ex-
ample, an application to support task X triggers another application to support task

1

Y. This means that one application knows about the existence of another applica-
tion. This is undesirable, because every time the underlying business process is
changed, applications need to be modified. Moreover, similar constructs need to
be implemented in several applications and it is not possible to monitor and con-
trol the entire workflow. Therefore, several software vendors recognized the need
for workflow management systems. A workflow management system (WFMS) is
a generic software tool which allows for the definition, execution, registration and
control of workflows (cf. [Law97]). At the moment many vendors are offering a
workflow management system. This shows that the software industry recognizes
the potential of workflow management tools.

UIMS UIMS

WFMS
DBMS

DBMS

DBMS
APPL
APPL APPL
APPL

OS OS OS OS
1960’s 1970’s 1980’s 1990’s

Figure 1: Workflow management systems in a historical perspective.

In order to become aware of the impact of workflow management in the near fu-
ture, it is useful to consider the evolution of information systems over the last four
decades (cf. [Aal96b]). Figure 1 shows the phenomenon of workflow management
in a historical perspective. The figure illustrates the evolution of information sys-
tems in the last four decades by describing the architecture of a typical information
system in terms of its components. In the sixties an information system was com-
posed of a number of stand-alone applications. For each of these applications an
application-specific user interface and database system had to be developed, i.e.,
each application had its own routines for user interaction and data storage and re-
trieval. In the seventies data was pushed out of the applications. For this purpose
database management systems (DBMSs) were developed. By using a database
management system, applications were freed from the burden of data management.
In the eighties a similar thing happened for user interfaces. The emergence of user
interface management systems (UIMSs) enabled application developers to push
the user interaction out of the applications. In our opinion workflow management
systems are the next step in pushing generic functionality out of the applications.
The nineties will be marked by the emergence of workflow software, allowing ap-
plication developers to push the business procedures out of the applications.
Figure 1 clearly shows that, in essence, the workflow management system is a ge-
neric building block to support business processes. Many information systems

2

could benefit from such a building block, because many organizations are start-
ing to see the need for advanced tools to support the design and execution of busi-
ness processes. There are several reasons for the increased interest in business pro-
cesses. First of all, management philosophies such as Business Process Reengi-
neering (BPR) and Continuous Process Improvement (CPI) stimulated organiza-
tions to become more aware of the business processes. Secondly, today’s organiza-
tions need to deliver a broad range of products and services. As a result the number
of processes inside organizations has increased. Consider for example mortgages.
A decade ago there were just a few types of mortgages, at the moment numerous
types are available. Not only the number of products and services has increased,
also the lifetime of products and services has decreased in the last three decades.
As a result, today’s business processes are also subject to frequent changes. More-
over, the complexity of these processes increased considerably. All these changes
in the environment of the information system in an average organization, have made
business processes an important issue in the development of information systems.
Therefore, there is a clear need for a building block named ‘workflow management
system’.

The main purpose of a workflow management system is the support of the def-
inition, execution, registration and control of processes. Because processes are
a dominant factor in workflow management, it is important to use an established
framework for modeling and analyzing workflow processes [HL91, Kou95, Law97].
In this paper we use a framework based on Petri nets. Petri nets are a well-founded
process modeling technique. The classical Petri net was invented by Carl Adam
Petri in the sixties ([Pet62]). Since then Petri nets have been used to model and ana-
lyze all kinds of processes with applications ranging from protocols, hardware, and
embedded systems to flexible manufacturing systems, user interaction, and busi-
ness processes. In the last two decades the classical Petri net has been extended
with color, time and hierarchy ([Aal94, Jen96]). These extensions facilitate the
modeling of complex processes where data and time are important factors. There
are several reasons for using Petri nets for workflow modeling:

formal semantics
A workflow process specified in terms of a Petri net has a clear and precise
definition, because the semantics of the classical Petri net and several en-
hancements (color, time, hierarchy) have been defined formally.

graphical nature
Petri nets are a graphical language. As a result, Petri nets are intuitive and
easy to learn. The graphical nature also supports the communication with
end-users.

3

expressiveness
Petri nets support all the primitives needed to model a workflow process. All
the routing constructs present in today’s workflow management systems can
be modeled. Moreover, the fact that states are represented explicitly, allows
for the modeling of milestones and implicit choices.

properties
In the last three decades many people have investigated the basic properties
of Petri nets. The firm mathematical foundation allows for the reasoning
about these properties. As a result, there is a lot of common knowledge, in
the form of books and articles, about this modeling technique.

analysis
Petri nets are marked by the availability of many analysis techniques. Clearly,
this is a great asset in favor of the use of Petri nets for workflow modeling.
These techniques can be used to prove properties (safety properties, invari-
ance properties, deadlock, etc.) and to calculate performance measures (re-
sponse times, waiting times, occupation rates, etc.). In this way it is possi-
ble to evaluate alternative workflows using standard Petri-net-based analysis
tools.

vendor independent
Petri nets provide a tool-independent framework for modeling and analyzing
processes. Petri nets are not based on a software package of a specific vendor
and do not cease to exist if a new version is released or when one vendor takes
over another vendor.

Other references where the use of Petri nets for workflow modeling is advocated
are [Aal96b, WR96, MEM94, EKR95, EN93, AH97]. In the remainder of this pa-
per we will show how Petri nets can be applied to the domain of workflow man-
agement. To do this, we first introduce the basic concepts of workflow manage-
ment and workflow management systems. Then we introduce the basic Petri-net
terminology. In section 4 we show how the workflow management concepts can be
mapped onto Petri nets. Section 5 is concerned with the analysis of workflow pro-
cesses specified in terms of a Petri net. Before we conclude, we describe a number
of Petri-net-based workflow tools to illustrate the use of Petri nets in this domain.

4

2 Workflow management (systems)
The term workflow management refers to the domain which focuses on the logis-
tics of business processes. There are also people that use the term office logistics.
The ultimate goal of workflow management is to make sure that the proper activi-
ties are executed by the right person at the right time. Although it is possible to
do workflow management without using a workflow management system, most
people associate workflow management with workflow management systems. The
Workflow Management Coalition (WfMC) defines a workflow management sys-
tem as follows ([WFM96]): A system that completely defines, manages, and ex-
ecutes workflows through the execution of software whose order of execution is
driven by a computer representation of the workflow logic. Other terms to char-
acterize a workflow management system are: ‘business operating system’, ‘work-
flow manager’, ‘case manager’ and ‘logistic control system’. On the one hand, it
is a pity that workflow management is often associated with workflow manage-
ment systems, because it limits the application domain of workflow management
in an unnecessary manner. (It is possible to do workflow management without us-
ing a workflow management system.) On the other hand, workflow management
systems give concrete form to the essential concepts, techniques, and methods for
workflow management.

Workflows are case-based, i.e., every piece of work is executed for a specific case.
Examples of cases are a mortgage, an insurance claim, a tax declaration, an order,
or a request for information. Cases are often generated by an external customer.
However, it is also possible that a case is generated by another department within
the same organization (internal customer). The goal of workflow management is
to handle cases as efficiently and effectively as possible. A workflow process is
designed to handle similar cases. Cases are handled by executing tasks in a spe-
cific order. The workflow process definition specifies which tasks need to be ex-
ecuted and in what order. Alternative terms for workflow process definition are:
‘procedure’, ‘flow diagram’ and ‘routing definition’. Since tasks are executed in a
specific order, it is useful to identify conditions which correspond to causal depen-
dencies between tasks. A condition holds or does not hold (true or false). Each task
has pre- and postconditions: the preconditions should hold before the task is exe-
cuted, and the postconditions should hold after execution of the task. Many cases
can be handled by following the same workflow process definition. As a result, the
same task has to be executed for many cases. A task which needs to be executed
for a specific case is called a work item. An example of a work item is: execute task
‘send refund form to customer’ for case ‘complaint sent by customer Baker’. Most
work items are executed by a resource. A resource is either a machine (e.g. a printer
or a fax) or a person (participant, worker, employee). In most offices the resources

5

are mainly human. However, because workflow management is not restricted to
offices, we prefer the term resource. Resources are allowed to deal with specific
work items. To facilitate the allocation of work items to resources, resources are
grouped into classes. A resource class is a group of resources with similar charac-
teristics. There may be many resources in the same class and a resource may be a
member of multiple resource classes. If a resource class is based on the capabilities
(i.e. functional requirements) of its members, it is called a role. If the classifica-
tion is based on the structure of the organization, such a resource class is called an
organizational unit (e.g. team, branch or department). A work item which is be-
ing executed by a specific resource is called an activity. If we take a photograph
of a workflow, we see cases, work items and activities. Work items link cases and
tasks. Activities link cases, tasks, and resources.
resource dimension

resource

activity

task

process dimension

work item
case
case dimension
Figure 2: A three dimensional view of a workflow.

Figure 2 shows that a workflow has three dimensions: (1) the case dimension, (2)
the process dimension and (3) the resource dimension. The case dimension sig-
nifies the fact that all cases are handled individually. From the workflow point
of view, cases do not directly influence each other. Clearly they influence each
other indirectly via the sharing of resources and data. In the process dimension,
the workflow process, i.e., the tasks and the routing along these tasks, is specified.
In the resource dimension, the resources are grouped into roles and organizational
units. We can visualize a workflow as a number of dots in the three dimensional
view shown in Figure 2. Each dot represents either a work item (case + task) or an
activity (case + task + resource). Figure 2 shows that workflow management is the
glue between the cases, the tasks, and the organization.

6

(a) A B C sequential
routing

B
(b) A D
parallel
routing
C

B
(c) A D conditional
routing
C

(d) A B C iterative
routing

Figure 3: Four routing constructs.

In this paper we focus on the first two dimensions, i.e., we concentrate on the work-
flow process which is defined to handle cases. We will not discuss human resource
aspects such as the classification of resources (organizational modeling) and the
mapping of resources to work items (scheduling) in much detail. We will just show
the mechanisms. A detailed discussion on resource management is beyond the
scope of this paper, because we concentrate on the application of Petri nets. Since
Petri nets are a process modeling technique, the application is restricted to the first
two dimensions.

For the first two dimensions, the routing of cases is one of the main issues. A
workflow process definition specifies how the cases are routed along the tasks that
need to be executed. Figure 3 shows the routing constructs identified by the Work-
flow Management Coalition (WfMC). The WfMC is an international organization
whose mission is to promote workflow and establish standards for workflow man-
agement systems. The WfMC was founded in 1993 and in January 1995 the WfMC
released a glossary which provides a common set of terms for workflow vendors,
end-users, developers, and researchers ([WFM96]). In this glossary four types of
routing are identified:
sequential
Tasks are executed sequentially if the execution of one task is followed by the
next task. In Figure 3(a) task B is executed after task A has been completed
and before task C is started.

7

parallel
In Figure 3(b) task B and task C are executed in parallel. This means that B
and C are executed at the same time or in any order. To model parallel rout-
ing, two building blocks are identified: (1) the AND-split and (2) the AND-
join. The AND-split in Figure 3(b) enables B and C to be executed after A
has been completed. The AND-join synchronizes the two parallel flows, i.e.,
task D may start after B and C have been completed.

conditional
In Figure 3(c) either task B or task C (exclusive OR) is executed. To model a
choice between two or more alternatives we use two building blocks: (1) the
OR-split and (2) the OR-join. If task A is executed, a choice is made between
B and C. Task D may start after B or C is completed.

iteration
Sometimes it is necessary to execute a task multiple times. In Figure 3(d)
task B is executed one or more times.

In Section 4, these routing constructs are mapped onto Petri nets. This way con-
cepts such as case, task, work item, activity and workflow process are defined in a
much more explicit manner. The issue of triggering is also discussed in Section 4.
The triggering concept is very important in the context of workflow management
([Joo94]).

workflow production
structured workflow
administrative
workflow
ad-hoc
workflow
collaborative
processes
unstructured

information process
centric centric

Figure 4: Workflow processes versus collaborative processes.

Not every business process is a workflow process. In our opinion, a workflow pro-

8

cess is characterized by three qualities. First of all, a workflow process is case-
driven. Secondly, the process itself is considered to be essential. Thirdly, the pro-
cess can be defined in an explicit manner. Many people use the term workflow
management in a broader sense. For example, sometimes groupware software tools
such as Lotus Notes and Microsoft Exchange are called workflow management
systems. This is not correct since these products do not support the workflow pro-
cess itself, they just allow people to collaborate by sending messages and sharing
information. Figure 4 shows the spectrum of case-based business processes. Pro-
duction workflow is concerned which highly structured processes with almost no
variations. This type of workflow needs to cope with many cases per day. The pro-
cessing of insurance claims is a typical example of production workflow. Adminis-
trative workflow corresponds to case-driven processes which follow a well-defined
procedure. Alternative routing of a case is possible, but needs to be predefined. Ad-
hoc workflow relates to processes where the procedure is not defined (completely)
in advance. Per case the procedure needs to be defined or an existing procedure
needs to be modified. Collaborative processes are outside the scope of our defini-
tion of workflow. In a collaborative process the emphasis is on communication and
the sharing of information rather than the definition of processes. For collaborative
processes it is not possible or not necessary to make the workflow processes ex-
plicit. Today’s workflow management systems such as COSA (COSA Solutions),
Flowmark (IBM), OPEN/Workflow (Eastman Software), Staffware (Staffware)and
Visual Workflow (FileNet) support production/administrative workflow. Just a few
products support ad-hoc workflow, e.g., Ensemble (FileNet). Collaborative pro-
cesses can be supported by groupware tools such as Lotus Notes and Microsoft
Exchange. Although these groupware tools do not support the logistic control of
workflow processes, they can be used as a communication layer in a proprietary
workflow system.

In this paper we restrict ourselves to real workflow management systems, i.e., sys-
tems to support production workflow, administrative workflow and/or ad-hoc work-
flow. The WfMC also focuses on this type of software tools. Many vendors and
users of these real workflow management systems have joined the WfMC to iden-
tify the common characteristics of these tools, to standardize terminology, and de-
fine standard architectures and interfaces. One of the first results achieved by the
WfMC was the definition of a reference model for the architecture of a workflow
system. However, before we describe the reference model, we stop at the subtle
difference between the term ‘workflow management system’ and the term ‘work-
flow system’. A workflow management system is a generic software product which
can be applied in many organizations, e.g., Staffware or COSA. However, if the
workflow management system is not installed, configured, and filled with data on
process definitions and applications, it cannot be used. Therefore, we reserve the

9

Figure 5: Reference model of the Workflow Management Coalition (WfMC).

term workflow system for the whole of the installed workflow management sys-
tem, the process definition data, the organizational data, the applications, the ap-
plication data, the database management system, the configuration files, and other
software components in the periphery of the actual workflow management system.
Figure 5 shows an overview of this reference model. The reference model de-
scribes the major components and interfaces within a workflow architecture. The
core of any workflow system is the workflow enactment service. The workflow
enactment service provides the run-time environment which takes care of the con-
trol and execution of the workflow. For technical reasons or managerial reasons
the workflow enactment service may use multiple workflow engines. A workflow
engine handles selected parts of the workflow and manages selected parts of the
resources. The process definition tools are used to specify and analyze workflow
process definitions and/or resource classifications. These tools are used at design
time. In most cases, the process definition tools can also be used as a BPR-toolset.
Most workflow management systems provide three process definition tools: (1)
a tool with a graphical interface to define workflow processes, (2) a tool to spec-
ify resource classes (organizational model), and (3) a simulation tool to analyze
a specified workflow. The end-user communicates with the workflow system via
the workflow client applications. An example of a workflow client application is
the well-known in-basket. Via such an in-basket work items are offered to the end
user. By selecting a work item, the user can execute a task for a specific case. If
necessary, the workflow engine invokes applications via interface 3. The adminis-

10

tration and monitoring tools are used to monitor and control the workflow. These
tools are used to register the progress of cases and to detect bottlenecks. Moreover,
these tools are used to set parameters, allocate people and handle abnormalities.
Via interface 4 the workflow system can be connected to other workflow systems.
To standardize the five interfaces shown in Figure 5, the WfMC aims at a common
Workflow Application Programming Interface (WAPI). The WAPI is envisaged as
a common set of API calls and related interchange formats which may be grouped
together to support each of the five interfaces (cf. [Law97]).

The architecture shown in Figure 5 has been adopted by most vendors. For most of
the interfaces, standards have been proposed. Unfortunately, these proposed stan-
dards are at a technical level with the emphasis on syntax instead of semantics.
There is no consensus at a conceptual level. Consider for example interface 1. The
syntax of the exchange format has been defined without formalizing the meaning
of states and essential building blocks such as the AND/OR-split/join. Therefore,
there is a need for a conceptual standard which clearly specifies the semantics of
the basic constructs needed. We claim that a workflow framework based on Petri
nets would be a good candidate for such a standard. In the remainder of this paper
we will substantiate this claim.

3 Petri nets
This section introduces the basic Petri net terminology and notations. Readers fa-
miliar with Petri nets can skip this section.1
Historically speaking, Petri nets originate from the early work of Carl Adam Petri
([Pet62]). Since then the use and study of Petri nets have increased considerably.
For a review of the history of Petri nets and an extensive bibliography the reader
is referred to [Mur89].

3.1 Classical Petri net
The classical Petri net is a directed bipartite graph with two node types called pla-
ces and transitions. The nodes are connected via directed arcs. Connections be-
tween two nodes of the same type are not allowed. Places are represented by circles
and transitions by rectangles.

1Note that states are represented by weighted sums and note the definition of (elementary) paths.

11

Definition 1 (Petri net) A Petri net is a triple (P T F ):
- P is a finite set of places,
- T is a finite set of transitions (P T = ),

- F (P T) (T P ) is a set of arcs (flow relation)
A place p is called an input place of a transition t iff there exists a directed arc from
p to t. Place p is called an output place of transition t iff there exists a directed arc
from t to p. We use t to denote the set of input places for a transition t. The nota-
tions t , p and p have similar meanings, e.g., p is the set of transitions sharing
p as an input place. Note that we restrict ourselves to arcs with weight 1. In the
context of workflow procedures it makes no sense to have other weights, because
places correspond to conditions.

At any time a place contains zero of more tokens, drawn as black dots. The state,
often referred to as marking, is the distribution of tokens over places, i.e., M 2
P ! IN. We will represent a state as follows: 1p1 + 2p2 + 1p3 + 0p4 is the state
with one token in place p1 , two tokens in p2 , one token in p3 and no tokens in p4 . We
can also represent this state as follows: p1 + 2p2 + p3 . To compare states we define
a partial ordering. For any two states M1 and M2 , M1 M2 iff for all p 2 P :
M1 (p) M2 (p)
The number of tokens may change during the execution of the net. Transitions are
the active components in a Petri net: they change the state of the net according to
the following firing rule:
(1) A transition t is said to be enabled iff each input place p of t contains at least
one token.

(2) An enabled transition may fire. If transition t fires, then t consumes one to-
ken from each input place p of t and produces one token in each output place
p of t.
Given a Petri net (P T F ) and a state M1 , we have the following notations:
- M1 ! M2: transition t is enabled in state M1 and firing t in M1 results in
t

state M2

- M1 ! M2 : there is a transition t such that M1 ! M2
t

- M1 ! Mn: the firing sequence = t1t2t3 : : : tn;1 leads from state M1 to
state Mn , i.e., M1 ! M2 ! ::: ! Mn
t t
1 tn;2 1

12

A state Mn is called reachable from M1 (notation M1 ! Mn ) iff there is a fir-
ing sequence = t1t2 : : : tn;1 such that M1 ! Mn . Note that the empty firing
sequence is also allowed, i.e., M1 ! M1 .

We use (PN M ) to denote a Petri net PN with an initial state M . A state M 0 is a
reachable state of (PN M ) iff M ! M 0 . Let us define some properties for Petri
nets.

Definition 2 (Live) A Petri net (PN M ) is live iff for every reachable state M0
and every transition t, there is a state M00 reachable from M 0 which enables t.

Definition 3 (Bounded, safe) A Petri net (PN M ) is bounded iff for each place
p there is a natural number n such that for every reachable state the number of
tokens in p is less than n. The net is safe iff for each place the maximum number
of tokens does not exceed 1.

Paths connect nodes by a sequence of arcs. A path is elementary if each node is
unique. For convenience, we also introduce the alphabet operator on paths.

Definition 4 (Path, elementary, alphabet) Let PN be a Petri net. A path C from
a node n1 to a node nk is a sequence hn1 n2 : : : nk i such that hni ni+1 i 2 F for
1 i k ; 1. (C ) = fn1 n2 : : : nk g is the alphabet of C . C is elementary iff
for any two nodes ni and nj on C, i 6= j ) ni 6= nj .

Definition 5 (Strongly connected) A Petri net is strongly connected iff for every
pair of nodes (i.e. places and transitions) x and y , there is a path leading from x
to y .

3.2 High-level Petri nets
The classical Petri net allows for the modeling of states, events, conditions, syn-
chronization, parallelism, choice, and iteration. However, Petri nets describing
real processes tend to be complex and extremely large. Moreover, the classical
Petri net does not allow for the modeling of data and time. To solve these prob-
lems, many extensions have been proposed. Three well-known extensions of the
basic Petri net model are: (1) the extension with color to model data, (2) the exten-
sion with time, and (3) the extension with hierarchy to structure large models. A
Petri net extended with color, time, and hierarchy is called a high-level Petri net.
In this paper we will use these extensions to model specific aspects. However, a
formalization of these aspects is beyond the scope of this paper. Therefore, we in-
troduce the three extensions in an informal manner.

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extension with color
Tokens often represent objects (e.g. resources, goods, humans) in the mod-
eled system. Therefore, we often want to represent attributes of these ob-
jects. If an insurance claim is modeled by a token in the Petri net, we want
to represent attributes such as the name of the claimant, identiﬁcation num-
ber, date, and amount. Since these attributes are not easily represented by a
token in a classical Petri net, we extend the Petri net model with colored or
typed tokens. In a colored Petri net each token has a value often referred to
as ‘color’. Transitions determine the values of the produced tokens on the
basis of the values of the consumed tokens, i.e., a transition describes the re-
lation between the values of the ‘input tokens’ and the values of the ‘output
tokens’. It is also possible to specify ‘preconditions’ which take the colors
of tokens to be consumed into account.

extension with time
For real systems it is often important to describe the temporal behavior of
the system, i.e., we need to model durations and delays. Since the classi-
cal Petri net is not capable of handling quantitative time, a timing concept is
added. There are many ways to introduce time into the Petri net. Time can
be associated with tokens, places, and/or transitions.

extension with hierarchy
Although timed colored Petri nets allow for a succinct description of many
business processes, precise speciﬁcations for real systems have a tendency
to become large and complex. This is the reason we provide a hierarchy
construct, called subnet. A subnet is an aggregate of a number of places,
transitions, and subsystems. Such a construct can be used to structure large
processes. At one level we want to give a simple description of the process
(without having to consider all the details). At another level we want to spec-
ify a more detailed behavior. The extension with hierarchy allows for such
an approach.

For a more elaborate discussion on these extensions and other kinds of high-level
Petri nets, the reader is referred to [Jen96, Aal94, Hee94].

14

4 Mapping workflow management concepts onto
Petri nets
Most workflow management systems and methodologies to support workflow man-
agement separate the modeling of the workflow process (How?) from the modeling
of the structure of the organization and the resources within the organization (By
whom?). The distinction between these two aspects is illustrated by Figure 2 which
relates the process dimension and the resource dimension. There are many reasons
for decoupling these two dimensions when specifying a workflow. The complex-
ity is reduced, reuse is stimulated, and it is possible to modify a process without
changing the organizational model (and vice-versa). In this section we will first
show that Petri nets are suitable for the modeling of the process dimension. Then
we will show how to incorporate the resource dimension.

4.1 Workflow process definition
In the process dimension, it is specified which tasks need to be executed and in
what order. Modeling a workflow process definition in terms of a Petri net is rather
straightforward: tasks are modeled by transitions, conditions are modeled by pla-
ces, and cases are modeled by tokens.
To illustrate the mapping of workflow management concepts onto Petri nets we
consider the processing of complaints. First the complaint is registered (task regis-
ter), then in parallel a questionnaire is sent to the complainant (task send questionn-
aire) and the complaint is evaluated (task evaluate). If the complainant returns the
questionnaire within two weeks, the task process questionnaire is executed. If the
questionnaire is not returned within two weeks, the result of the questionnaire is
discarded (task time out). Based on the result of the evaluation, the complaint is
processed or not. The actual processing of the complaint (task process complaint)
is delayed until the questionnaire is processed or a time-out has occurred. The pro-
cessing of the complaint is checked via task check processing. Finally, task archive
is executed.
Figure 6 shows a workflow process definition for the processing of complaints spec-
ified in terms of a Petri net. The tasks register, send questionnaire, evaluate, pro-
cess questionnaire, time out, process complaint, check processing and archive have
been modeled by transitions. The transitions processing OK and processing NOK
have been added to model the two possible outcomes of executing task check pro-
cessing. The transitions no processing and processing required have been added
for similar reasons. To model the states between tasks, conditions have been added.
Each condition is modeled by a place. For example, place c2 corresponds to the
condition ‘ready to evaluate complaint’. Condition c5 is true (i.e. place c5 con-

15

time_out

c5

c1 send_questionnaire c3 archive
process_questionnaire

i evaluate no_processing o
register

c2 c4 c6
processing_OK
processing_required process_complaint check_processing

c7 c8 c9

processing_NOK

Figure 6: A Petri net for the processing of complaints.

tains a token) if the questionnaire has been processed or a time-out has occurred.
Note that c5 is a prerequisite for the task archive and the task process complaint.
Condition i is the start condition and condition o is the end condition.
The workflow process definition shown in Figure 6 models the life-cycle of a sin-
gle case. In general, there are many cases which are handled according to the same
workflow process definition. Each of these cases corresponds to one or more to-
kens. If tokens of multiple cases reside in the same Petri net, then these tokens
may get mixed. For example, transition archive may consume two tokens which
correspond to different cases. Clearly, this is undesirable. There are two ways to
solve this problem. First of all, it is possible to use a high-level Petri net where
each token has a value (color) which contains information about the identity of the
corresponding case (case identifier). Transitions are not allowed to fire if the case
identifiers of the tokens to be consumed do not match, i.e., a precondition is used
which inspects and compares token values. Figure 7 shows a high-level Petri net
with case identifiers. The dotted lines are used to associate tokens to cases, e.g.,
the token in place c1 has value 3 thus linking it to case 3. Another way to solve
this problem is the following. Each case corresponds to a unique instance of the
Petri net. If there are n cases, then there are n instances of the Petri net. One can
think of such an instance as a layer. If these layers are put on top of each other, it is
possible to see the cases in the same diagram. The latter is interesting from a man-
agement point of view, because one gets an overview of the state of the workflow.
For example, if a place contains a lot of tokens, this might indicate a bottleneck.
In the remainder of this paper, we consider Petri nets which describe the life-cycle
of one case in isolation.

16

case 3
time_out
case 1
case 6 case 2
c5

c1 send_questionnaire c3 archive
process_questionnaire

i evaluate no_processing o
register

c2 c4 c6
case 4
processing_OK
processing_required process_complaint check_processing

c7 c8 c9

case 5
processing_NOK

Figure 7: Tokens have a case identifier which allows for the separation of cases.

A Petri net which models a workflow process definition (i.e. the life-cycle of one
case in isolation) is called a WorkFlow net (WF-net). A WF-net satisfies two re-
quirements. First of all, a WF-net has one input place (i) and one output place
(o). A token in i corresponds to a case which needs to be handled, a token in o
corresponds to a case which has been handled. Secondly, in a WF-net there are
no dangling tasks and/or conditions. Every task (transition) and condition (place)
should contribute to the processing of cases. Therefore, every transition t (place p)
should be located on a path from place i to place o. The latter requirement corre-
sponds to strongly connectedness if o is connected to i via an additional transition
t (see Figure 23).
Definition 6 (WF-net) A Petri net PN = ( P T F ) is a WF-net (WorkFlow net)
if and only if:
(i) PN has two special places: i and o. Place i is a source place: i = . Place
o is a sink place: o = .

(ii) If we add a transition t to PN which connects place o with i (i.e. t = fog
and t = fig), then the resulting Petri net is strongly connected.

Places in the set P correspond to conditions, transitions in the set T correspond to
tasks. Note that the requirements stated in Definition 6 are minimal requirements.
Even if these requirements are satisfied it is still possible to define a workflow pro-
cess definition with potential deadlocks and/or livelocks.

Tokens in a WF-net represent the workflow state of a single case. The workflow

17

state contains partial information about the state of a case. In addition the case has
workflow attributes and application data. The workflow state corresponds to the
distribution of tokens over the places (marking). Consider for example Figure 7.
The workflow state of case 5 is c3 + c7. A workflow attribute is a specific piece of
information used for the routing of a case. One can think of a workflow attribute as
a control variable or a logistic parameter. A workflow attribute may be the age of
the complainant, the department responsible for the complaint, or the registration
date. We will also use the term case attribute to refer to the workflow attribute of
a specific case. The classical Petri net PN = (P T F ) abstracts from these work-
flow attributes. However, in a high-level Petri net, the extension with color can be
used to model workflow attributes. The application data is not used to manage the
workflow, it is used to execute the task. The application data is outside the scope
of the workflow process definition and the workflow management system has no
knowledge of this information. (Nevertheless, often there are workflow attributes
which can be derived from the application data.) Examples of application data are
the address of the complainant and the evaluation report.

4.2 Routing constructs
In the process dimension, building blocks such as the AND-split, AND-join, OR-
split and OR-join are used to model sequential, conditional, parallel, and iterative
routing (WfMC [WFM96]). Clearly, a WF-net can be used to specify the routing of
cases. In Section 2, four types of routing have been identified: sequential, parallel,
conditional, and iteration.

A B C
c1 c2 c3 c4

Figure 8: Sequential routing.

Sequential routing is used to deal with causal relationships between tasks. Con-
sider two tasks A and B. If task B is executed after the completion of task A, then
A and B are executed sequentially. Figure 8 shows that sequential routing can be
modeled by adding places. Place c2 models the causal relationship between task
A and task B, i.e., place c2 represents a postcondition for task A and a precondition
for task B. Place c3 models the causal relationship between task B and task C.

Parallel routing is used in situations where the order of execution is less strict. For
example, two tasks B and C need to be executed but the order of execution is ar-
bitrary. To model such a parallel routing, two building blocks are used: (1) the

18

AND-split AND-join
B
A c2 c4 D
c1 c6
C
c3 c5

Figure 9: Parallel routing.

AND-split and (2) the AND-join. Figure 9 shows that both building blocks can
be modeled by ordinary transitions. One can think of these transitions as control
tasks that have been added for routing purposes. However, a normal task can also
act as an AND-split and/or an AND-join. The execution of AND-split A enables
both task B and task C. AND-join D is enabled after execution both B and C, i.e., D
is used to synchronize two subflows. As a result, task B and task C are executed in
parallel. This means that B and C are executed in arbitrary order. It is even possi-
ble that the execution of B and C coincides, i.e., for one case, tasks overlap in time.
In several workflow management systems, it is not possible to execute two tasks
for the same case at the same time. In this case, we use the term semi-parallel. If
semi-parallel routing is used in Figure 9, then B is executed before C or vice versa,
i.e., interleaving semantics are used to interpret the workflow process definition.
Sometimes, semi-parallel routing is used to avoid serious technical problems. For
example, for each case, applications and/or tasks in the workflow management sys-
tem share data. In this case, the locking mechanism in the database mangement
system may prevent tasks to be executed concurrently for the same case.

OR-split OR-join
B
A D
c1 c2 c3 c4
C

Figure 10: Conditional routing.

Conditional routing is used to allow for a routing which may vary between cases.
In this way, the routing of a case may depend on the workflow attributes of a case,
the behavior of the environment, or the workload of the organization. To model
a choice between two of more alternatives, two building blocks are used: (1) the
OR-split and (2) the OR-join (in both cases an exclusive OR). An OR-split can
be modeled by a place with multiple outgoing arcs, an OR-join is modeled by a

19

place with multiple ingoing arcs. Figure 10 shows the situation where task A is
followed by either task B or task C, i.e., a choice is made between B and C. The
execution of one of these two tasks is followed by the execution of task D. Place
c2 is a precondition for both B and C. However, just one of these two tasks will be
executed for the case in place c1.
If c2 contains a token, a non-deterministic choice is made between B and C. How-
ever, the choice between alternatives often depends on workflow attributes. If the
choice is based on workflow attributes, it is a deterministic choice. For example,
the routing of an insurance claim may depend on the compensation costs. There-
fore, a workflow attribute is used to take into account the compensation costs. If
these costs exceed a certain amount, additional checks are necessary. The routing
of a traffic violation may depend on the type of the traffic violation represented
by the corresponding workflow attribute. There are two ways to model a choice
based on workflow attributes. (Recall that the extension with color is used to mo-
del workflow attributes.) We can use the construct shown in Figure 10 and add a
precondition (i.e. an additional enabling requirement based on one or more work-
flow attributes) to each of the tasks such that either B or C is enabled if c2 contains
a token. Another way to model a deterministic choice between B or C is shown in

explicit OR-split OR-join
x>0 B
A c2 D
c1 c4 c5
x <= 0 C
c3

Figure 11: Explicit choice between B and C based on workflow attribute x.

Figure 11. Transition A has two output places c2 and c3. Transition A produces ei-
ther a token in c2 or c3. The choice between c2 or c3 is based on workflow attribute
x. If x is positive, task B will be executed, otherwise task C. A special symbol is
used to denote the fact that task A is an OR-split (exclusive OR). Note that the non-
deterministic choice in Figure 10 differs from the choice in Figure 11 with respect
to the moment of choice. In Figure 11 the choice is made the moment task A is com-
pleted, in Figure 10 the choice is made the moment B or C is executed. We will
use the term explicit OR-split for a choice based on workflow attributes. The term
implicit OR-split is reserved for the situation where the moment of choice is as late
as possible. For workflow modeling it is of the utmost importance to distinguish
between implicit and explicit OR-splits.

In Figure 11 we introduced a special notation for an explicit OR-split. We will also

20

AND-split AND-join

implicit implicit
OR-split OR-join

explicit explicit
OR-split OR-join

Figure 12: The building blocks for workflow modeling.

denote the fact that a task is an AND-split, an AND-join, and/or an OR-join. Fig-
ure 12 lists the main constructs. The AND-split and the AND-join correspond to
the normal behavior of a transition in a classical Petri net. The implicit OR-split
and OR-join are modeled by places. The explicit OR-split is modeled by a tran-
sition which produces one token in one of its output places, i.e., it is an exclusive
OR (XOR). The place is selected on the basis of the workflow attributes. The ex-
plicit OR-join is modeled by a transition which is enabled if one of the input places
contains a token. In general, the explicit OR-join can be modeled by an implicit
OR-join (i.e. a place). There is no compelling need to distinguish between implicit
and explicit OR-joins. Therefore, we will avoid the use of explicit OR-joins in this
paper. However, the distinction between the implicit OR-split and the explicit OR-
split is of practical relevance and will be discussed in more detail when the concept
of triggering is introduced.

The last form of routing is iteration. Iteration can be modeled using the building
blocks shown in Figure 12. Consider for example the workflow process definition
shown in Figure 13. Task C is a control task which checks the result of task B.
Based on this check, task B may be executed once more. In Figure 13 task B is ex-
ecuted one or more times. It is also possible to specify that task B is executed zero
or more times. Iteration is often considered to be an undesirable form of routing,

21

A B C
c1 c2 c3 c4

Figure 13: Iteration: B may be executed multiple times.

because it corresponds to the repeated execution of the same task without making
any real progress. Unfortunately, there are many situations where iteration cannot
be avoided. For example, the information supplied by the customer is incomplete
or a request is refused.

4.3 Triggering
A workflow process definition, such as the one shown in Figure 6, specifies how a
case is routed, i.e., which tasks need to be executed and in what order. For an arbi-
trary case in a specific state (workflow state and workflow attributes) it is specified
which tasks can be executed. It is important to note that the fact that if a task can
be executed for a specific case, then this does not mean that the task is executed
directly. For example, if a task is to be executed by an employee, then the em-
ployee has to be available and willing to execute the task. If the employee is ill,
on holidays or having lunch, then the task will not be executed. Another exam-
ple is the processing of a form which is returned by a customer. If the customer
does not return the form, the corresponding task cannot be executed. These exam-
ples show that for many tasks additional conditions (e.g. availability of resources
or information) need to be satisfied. The execution of these tasks cannot be forced
by the workflow management system. The workflow management system cannot
force customers to return forms nor can it force employees to execute specific tasks.
The workflow management system is not in complete control, it just supports the
workflow. Therefore, it is important to differentiate between the enabling of a task
and the execution of a task. Since the enabling of a task does not imply that the task
will be executed (immediately), it is crucial to have this distinction. Therefore, we
introduce the concept of triggering.
A trigger is an external condition which leads to the execution of an enabled task.
The execution of a task instance for a specific case starts the moment the task in-
stance is triggered. A task instance can only be triggered if the corresponding case
is in a state which enables the execution of the task. In this paper, we distinguish
between four types of tasks.
Automatic: a task is triggered the moment it is enabled. This kind of trig-
gering is used for tasks which are executed by an application which does not

22

automatic message

user time

Figure 14: Four types of triggering.

require human interaction.

User: a task is triggered by a human participant, i.e., a user selects an enabled
task instance to be executed. In a workflow management system each user
has a so-called ‘in-basket’. This in-basket contains tasks instances that are
enabled and may be executed by the user. By selecting a task instance the
corresponding task instance is triggered.

Message: an external event (i.e. a message) triggers an enabled task instance.
Examples of messages are telephone-calls, fax messages, e-mails or EDI
messages.

Time: an enabled task instance is triggered by a clock, i.e., the task is exe-
cuted at a predefined time. For example, the task ‘remove document’ is trig-
gered if a case is trapped in a specific state for more than 15 hours.

Only for automatic tasks do the enabling and the actual start of the execution co-
incide. In the workflow process definition we will use the symbols shown in Fig-
ure 14 to denote the type of trigger required.

Figure 15 shows the workflow process definition for the processing of complaints
using the building blocks introduced in Figure 12. The tasks no processing, pro-
cessing required, processing OK and processing NOK (see Figure 6) are replaced
by the OR-split evaluate and the OR-split check processing. The diagram is also
extended with triggering information. The tasks register, evaluate, process compl-
aint and check processing require a user trigger because they are executed by hu-
man resources. The tasks send questionnaire and archive are executed by an appli-
cation which does not require human interaction. The task process questionnaire
can only be executed if the complainant returns the form, i.e., an external trigger is
required to execute this task. The task time out requires a time trigger. If the work-
flow state of a case is such that there is a token in c3 (Figure 15), then there are two
possibilities: either process questionnaire is executed because the complainant re-
turns the form in time or time out is executed the moment a certain period of time

23

time_out

c5

c1 send_questionnaire c3 process_questionnaire

i evaluate o
register archive

c2 c6

c7 check_processing

process_complaint c8

Figure 15: A workflow process definition extended with triggering information.

expires. Note that the moment of choice between process questionnaire and time out
is as late as possible. Therefore, an implicit OR-split is used instead of an explicit
OR-split.

The introduction of triggers can be used to illustrate the essence of the difference
between the implicit and the explicit OR-split. If the implicit OR-split in Figure 15
is replaced by an explicit OR-split (i.e. send questionnaire chooses between pro-
cess questionnaire and time out), the behavior changes dramatically. For example,
it is possible that forms which are returned in time are rejected, or cases are blocked
if some of the forms are not returned at all. Another example is given in Figure 16.
In both process definitions the execution of task A is followed by the execution of
B or C. In the first process definition (a), the moment of choice is as late as pos-
sible. After the execution of A, there is a ‘race’ between B and C. If the external
message required for task C arrives before someone starts executing task B, then C
is executed, otherwise B. In the second workflow process definition (b), the choice
is fixed after the execution of A. If task B is selected, then the arrival of the exter-
nal message has no influence. If C is selected, then B cannot be used to bypass C.
Figure 16 shows the importance of the explicit representation of triggers, states,
and the moment of choice. Many workflow management systems abstract from
states between subsequent tasks, therefore they have problems modeling implicit
OR-splits. They also have problems modeling milestones such as c5 in Figure 15.
Clearly, the explicit representation of states is important. Fortunately, Petri nets
allow for the explicit representation of states in a very elegant manner.

24

implicit OR-split
B
A D
c1 c2 c3 c4
C

(a)

explicit OR-split
B
c2
A D
c1 c4 c5
C
c3
(b)

Figure 16: An example to illustrate the difference between (a) the implicit OR-split
and (b) the explicit OR-split.

4.4 Tasks, work items and activities
A task corresponds to a generic piece of work. A task is not defined for a specific
case, but for a type of cases, i.e., a task may be executed for many cases. To avoid
confusion between (1) a task, (2) the enabling of a task, and (3) the execution of a
task, we introduce two additional terms: work item and activity. A work item is a
task which is enabled for a specific case, i.e., a work item corresponds to a concrete
piece of work. In a sense, a work item is the combination of a task, a case and a trig-
ger (optional). In a workflow management system, work items which correspond
to interactive tasks are offered to the user via the so-called in-basket. An activity is
the actual execution of a work item, i.e., a task is executed for a specific case. An
activity combines a task, a case, a trigger and/or a resource (optional). It is easy to
map the terms task, work item, and activity onto Petri-net terminology. A tasks cor-
responds to a transition, a work item corresponds to an enabled transition (binding)
and an activity corresponds to a transition firing. Consider for example Figure 15.
Transition process complaint corresponds to a task. If both c5 and c7 contain a to-
ken with case-identifier 91212123, then the enabled transition process complaint
corresponds to a work item. If process complaint fires while consuming the two
tokens with case-identifier 91212123, then this firing corresponds to an activity.

One can think of a trigger as an additional condition which needs to be satisfied
before a task can be executed. If we model this in terms of Petri nets, a trigger
corresponds to a token in an additional input place of the task. Thus far, we have

25

c1 c3
t

c2 c4

trigger_place

start

commit
c1 c3

c2

c2 rollback c4

Figure 17: The low-level behavior of a task.

modeled tasks by transitions. By mapping tasks onto transitions we abstract from
the internal behavior of a task. This abstraction is convenient for workﬂow model-
ing. However, if we consider a task in more detail, then it is clear that the execution
of a task takes time, i.e., time elapses between start and completion. In fact, it is
possible that during the execution of a task some anomalies occur, e.g., an appli-
cation crashes, the database is down, or information is missing. Therefore, it is
possible that the execution of a task is postponed or canceled. Figure 17 shows a
simple Petri net model of the low-level behavior of a task. The start of an activity
(transition start ﬁres) is followed by either a commit (transition commit) or a roll-
back (transition rollback). Note that the trigger is modeled by a token in the place
trigger place.

One can think of a task as a Logical Unit of Work (LUW) and an activity as a trans-
action. Just like a transaction, an activity should satisfy the well-known ACID
properties. The acronym ACID stands for:

atomicity
An activity is executed successfully (commit) or is rolled back completely,
i.e., a task cannot be completed partially.

26

consistency
The execution of an activity leads to a consistent state.
isolation
The effect of the execution of an activity in parallel with other activities is
equal to the effect of the execution of one activity in isolation.

durability
The result of a committed activity cannot get lost.
The ACID properties impose technical constraints on the size of a task. Choosing
tasks which have the ‘right’ size is one of the main issues in workflow modeling.
If the tasks are too small, then there is a lot of overhead (setup times) and the work-
flow becomes too complex to manage. If the tasks are too large, then it may be-
come a problem to execute a task in one go, because it is not possible to commit
a partially completed task or put parts of the task out to contract. Moreover, the
management of resources, i.e., the allocation of work items to users, is not fine-
grained enough if the tasks are too large to allow for specialization. Note that the
granularity of the management of resources is determined by the size of each task.

4.5 Resource classification
Clearly, Petri nets are well-suited for the modeling of workflow process definitions.
However, thus far we focused on the process dimension and not on the resource di-
mension. The resource dimension is concerned with organizational issues such as
the formation of teams and the authorization of users. Most workflow management
systems provide a design tool to model the organization. These tools can be used to
structure the resource dimension and facilitate the specification of the rules used to
allocate work items to resources. We will use the term resource for an actor which
is able to execute specific tasks. In most environments where workflow manage-
ment systems are used, the resources are mainly human. However, as indicated
in Section 2, we prefer the term resource over employee or participant, because
workflow management is not restricted to offices.
For each task, we need to specify who is allowed to execute the task. However, ex-
plicitly linking resources and tasks is considered to be harmful. If a task is linked to
a specific user, then the task will be blocked if the user is absent. The use of links
to specific resources reduces flexibility. Moreover, the workflow process defini-
tion needs to be modified each time a new employee is hired (or an existing em-
ployee is discharged). To avoid links to specific resources, resources are grouped
into classes. A resource class is a group of resources with similar characteris-
tics. Note that a resource may be a member of multiple resource classes. Consider
for example Figure 18. There are four resource classes: Complaints department,

27

Complaints_department
Processing_staff

Evaluators Support_staff
Suzan Harry Tracy
Mike

Marian Pete
Kate Bill

John
Eric

Figure 18: Resource classification.

Evaluators, Processing staff and Support staff. Marian is a member of Evaluators,
Processing staff, and Complaints department, but she is not a member of the re-
source class Support staff. The resource classification shown in Figure 18 can be
used to specify which resources are allowed to execute the four user tasks in Fig-
ure 15. Tasks register, evaluate, process complaint and check processing should
be executed by a member of the class Complaints department. Moreover, regis-
ter requires a member of the class Support staff, evaluate requires a member of
the class Evaluators, process complaint requires a member of the class Process-
ing staff, and check processing requires a member of the class Evaluators. Note
that without explicitly linking tasks and resources it is specified that Marian is one
of the three persons allowed to execute the task check processing.

In Section 2, two types of resource classes were introduced: roles and organiza-
tional units. If a resource class is based on the capabilities (i.e. functional require-
ments) of its members, it is called a role. The resource classes Support staff, Eval-
uators and Processing staff are examples of roles. If the classification is based on
the structure of the organization, such a resource class is called an organizational
unit (e.g. team, branch or department). The class Complaints department is an ex-
ample of resource class which is based on the structure of the organization instead
of the capabilities of its members. Many workflow management systems associate
a role and an organizational unit with each task. This means that the task should be

28

organisational units

roles

resource
Figure 19: Resource classification: a resource is a member of organizational units
and roles.

executed by a resource which is a member of both a resource class based on func-
tional requirements (role) and a resource class based on the structure of the organi-
zation (organizational unit). Figure 19 illustrates the orthogonal relation between
roles and organizational units.

By associating a role and an organizational unit with each task, the number of re-
sources allowed to execute this task is reduced to the intersection of both classes.
Sometimes more advanced concepts are needed to specify who is allowed to exe-
cute a specific work item. Sometimes the role or the organizational unit associated
with a task is case-dependent. For example, insurance claims with estimated com-
pensation costs of more than 1000 dollars are handled by a senior employee, or
complaints about a specific department are handled by team A. It is also possible
that specific resources are excluded because they have executed related tasks. For
example, the tasks evaluate and check processing in Figure 15 should be executed
by different resources. This means that if Marian executed the task evaluate for a
specific case, she is not allowed to execute check processing for the same case (i.e.
it should be executed by Mike or Eric). We use the term ’separation of functions’
for this additional requirement.

29

4.6 Resource management
The resource classification and more advanced concepts such as the separation of
functions are used to specify who is allowed to execute a work item. If there are
multiple resources allowed to execute a work item, a choice has to be made. There
are two mechanisms to resolve this choice:

push control
The workflow management system makes a choice and sends each work item
to a specific user, i.e., for each work item a resource is chosen. The choice
may be based on statistical information, work load, or simple heuristics.

pull control
The workflow management system sends a copy of each work item to every
user who is allowed to execute it. The moment one user selects a work item,
all other copies disappear.

In most situations, pull control is the preferred mechanism to distribute work items.
Note that push control reduces the flexibility by linking work items to specific re-
sources. The users of the workflow management system often dislike push control
because they feel controlled by the system.
The choice between multiple resources allowed to execute a work item is not the
only decision to be made. If there are many work items, the order in which these
work items have to be executed needs to be decided. Well-known queuing disci-
plines known from operations management ([Wil89]) can be used to order pending
work items: FIFO (first in first out), LIFO (last in first out), SPT (shortest process-
ing time), SRPT (shortest remaining processing time), EDD (earliest due date) and
PRIO (tasks with priority go first). If push control is used, the workflow manage-
ment system will force the execution of work items in a specific order. If pull con-
trol is used, the user can deviate from the order suggested by the system. Note that
the ordering of work items and the selection of resources are closely related.

Each time a user executes a work item, a setup is required both for the case and
the task. To reduce setup times some workflow management systems allow for
chained execution and piled execution. Chained execution corresponds to the ex-
ecution of multiple subsequent tasks for the same case in one go and by one user.
Consider for example the workflow process shown in Figure 15. If the tasks regis-
ter, send questionnaire, and evaluate can be executed by a specific resource, then
chained execution would mean that if the resource starts the task register, the two
other tasks will follow automatically (for the same case). Chained execution al-
lows tasks to be clustered into macrotasks. Piled execution corresponds to the re-
peated execution of one task for multiple cases. For example, a resource executes

30

the task register for a batch of cases. Chained execution reduces the overall setup
time needed to get acquainted with the case. Piled execution helps the user to build
routine.
A concept which is closely related to chained execution is case management. If
case management is used, then each case has a case manager. The case manager is
responsible for the case and executes as many tasks for the case as possible. The
use of case management has two benefits: setup times are reduced and the case
manager serves as a contact for the customer whose case is handled. Only a few
workflow management systems support advanced concepts such as chained exe-
cution, piled execution, and case management.

4.7 Summary
In this section we introduced a number of workflow concepts and showed how
these concepts can be mapped onto Petri nets. The four routing constructs identi-
fied by the WfMC have been mapped onto WF-nets. The Petri-net formalism also
allowed us to experience the subtle difference between the implicit OR-split and
the explicit OR-split. More advanced topics such as milestones, triggers, and the
difference between tasks, work items, and activities have been illustrated by using
some examples. These examples show that the Petri-net formalism is well-suited
to deal with the first two dimensions shown in Figure 2. To establish a link be-
tween the workflow process definition defined in terms of a WF-net and the third
dimension (resource dimension), we discussed the classification of resources and
allocation of resources to work items (resource management).

5 Analysis of workflows
In this section we focus on the analysis of workflows. We start with an overview of
the various types of workflow analysis. Then we concentrate on a a specific type of
analysis: verification. For this purpose, we will introduce a notion of correctness
called ‘soundness’ and devote the rest of this section to Petri-net-based analysis
techniques to establish soundness. The results presented in this section will illus-
trate the potential of Petri nets in the workflow domain.

5.1 Introduction
The correctness, effectiveness, and efficiency of the business processes supported
by the workflow management system are vital to the organization. A workflow
process definition which contains errors may lead to angry customers, back-log,
damage claims, and loss of goodwill. Flaws in the design of a workflow definition

31

may also lead to high throughput times, low service levels, and a need for excess
capacity. This is why it is important to analyze a workflow process definition be-
fore it is put into production. Basically, there are three types of analysis:

validation, i.e., testing whether the workflow behaves as expected,

verification, i.e., establishing the correctness of a workflow, and

performance analysis, i.e., evaluating the ability to meet requirements with
respect to throughput times, service levels, and resource utilization.

Validation can be done by interactive simulation: a number of fictitious cases are
fed to the system to see whether they are handled well. For verification and perfor-
mance analysis more advanced analysis techniques are needed. Fortunately, many
powerful analysis techniques have been developed for Petri nets ([Mur89]). Linear
algebraic techniques can be used to verify many properties, e.g., place invariants,
transition invariants, and (non-)reachability. Coverability graph analysis, model
checking, and reduction techniques can be used to analyze the dynamic behavior
of a Petri net. Simulation and Markov-chain analysis can be used for performance
evaluation (cf. [MBea95]). The abundance of available analysis techniques shows
that Petri nets can be seen as a solver independent medium between the design of
the workflow process definition and the analysis of the workflow.

Today’s workflow management systems give limited support to performance anal-
ysis. Most workflow management systems provide a rudimentary simulator or pro-
vide a gateway to a simulation tool. Simulation can be used to estimate key per-
formance indicators by experimenting with the specified workflow under the as-
sumption of a specific behavior of the environment. Examples of key performance
indicators are: average throughput time of cases, average waiting time, occupation
rates of resources, service levels, and the average number of pending cases.
Most workflow management systems do not give any support for the verification
of workflows. As a result, workflow process definitions become operational before
they are thoroughly checked for correctness. This often results in runtime errors
which need to be repaired on-the-fly at high costs. Both manufacturers and users
of workflow management systems see the need for analysis tools which take care
of the verification of workflows. Unfortunately, most manufacturers do not have
the technology to build such tools. In the remainder of this section we will show
that workflows specified in terms of Petri nets can be verified using state-of-the-art
analysis techniques.

32

5.2 Soundness property
Consider the WF-net shown in Figure 20. It is easy to see that this workflow pro-
cess definition contains several deficiencies. If time out 1 and processing 2 fire,
or time out 2 and processing 1 fire, then the WF-net will not terminate properly
because a token gets stuck in c5 or c4. If time out 1 and time out 2 fire, then the
task processing NOK will be executed twice and because of the presence of two
tokens in o the moment of termination is not clear.

time_out_1
c3 processing_NOK

c1
processing_1

c4
i time_out_2 o
register

c5
c2
processing_OK
processing_2

Figure 20: Another WF-net for the processing of complaints.

Clearly the WF-net shown in Figure 20 is not correct, but what is the definition
of correctness? The correctness criterion we use in this paper is a set of minimal
requirements any workflow process definition should satisfy. First of all, the work-
flow process definition should satisfy the two requirements listed in Definition 6:
(1) a WF-net has a source place i (start condition) and a sink place o (end condi-
tion), and (2) each task/condition is on a path from i to o. These requirements can
verified statically, i.e., they only relate to the structure of the Petri net. However,
there is a third requirement which should be satisfied:

For any case, the procedure will terminate eventually and the moment
the procedure terminates there is a token in place o and all the other
places are empty.

Moreover, there is a fourth requirement:

There should be no dead tasks, i.e., it should be possible to execute an
arbitrary task by following the appropriate route though the WF-net.

These two additional constraints correspond to the so-called soundness property.

33

Definition 7 (Sound) A procedure modeled by a WF-net PN =(P T F ) is sound
if and only if:

(i) For every state M reachable from state i, there exists a firing sequence lead-
ing from state M to state o. Formally:2

8M (i ! M ) ) (M ! o)
(ii) State o is the only state reachable from state i with at least one token in place
o. Formally:
8M (i ! M ^ M o) ) (M = )o
(iii) There are no dead transitions in (PN i). Formally:
8t2T 9M M 0 i ! M ! M 0
t

Note that the soundness property relates to the dynamics of a WF-net. The first
requirement in Definition 7 states that starting from the initial state (state i), it is
always possible to reach the state with one token in place o (state o). If we as-
sume fairness (cf. [Val87, Mur89]) then the first requirement implies that eventu-
ally state o will be reached. The fairness assumption is reasonable in the context
of workflow management: all choices are made (implicitly or explicitly) by appli-
cations, humans, or external actors. Clearly, they should not introduce an infinite
loop. (We will come back to issue of fairness.) The second requirement in Defini-
tion 7 states that the moment a token is put in place o, all the other places should
be empty. Sometimes the term proper termination is used to describe the first two
requirements [GCEV72]. The third and last requirement states that there are no
dead transitions (tasks) in the initial state i, i.e., for each transition t it is possible
to reach (starting from i) a state where t is enabled.

Definition 7 assumes that the workflow is specified in terms of a WF-net. Recall
that a WF-net is a classical Petri net which satisfies certain properties. However,
we have enhanced the workflow process definition with triggers and workflow att-
ributes. The analysis techniques presented in the remainder of this paper will ab-
stract from this additional information. Triggers are simply removed. An AND-
split/AND-join corresponds to a normal transition in the Petri net. Tokens have
no value (uncolored). However, we cannot map an OR-split and/or OR-join task
onto a single transition. An OR-split is unfolded into a small network with a tran-
sition for each alternative. An OR-join is also replaced by two or more transitions.
2Note that there is an overloading of notation: the symbol i is used to denote both the place i
and the state with only one token in place i (see Section 3).

34

t t

t_a

t

t_b

t_a

t

t_b

Figure 21: Removing triggers and unfolding tasks to obtain a WF-net.

Figure 21 shows the translation into a WF-net by removing triggers and unfolding
tasks.
There are several reasons for abstracting from triggers and workflow attributes.
First of all, the behavior of the environment cannot be modeled completely. The
environment (e.g. employees and customers) generates triggers and sets workflow
attributes. For simulation purposes it is necessary to model the behavior of the en-
vironment to a certain extent. However, for verification purposes it is very danger-
ous to use an explicitly modeled environment. If the real environment differs from
the modeled environment, verification is pointless. Incorrect assumptions about
the environment, may hide errors in the design of a workflow process definition.
Therefore, we abstract from triggers and workflow attributes. We just assume that
the environment is willing to generate triggers and each choice is considered to be
non-deterministic. Consider for example the task evaluate in Figure 15. This task
is replaced by two transitions to model the two possible outcomes of the evalua-
tion. In reality, the choice is based on workflow attributes, application data and/or
the behavior of the evaluator. Clearly, this cannot be modeled completely. There-
fore, we consider the choice to be a non-deterministic one. There are other reasons
for abstracting from the triggers and workflow attributes. If we are able to prove
soundness for the situation without triggers and workflow attributes, it will also
hold for the situation with triggers and workflow attributes. Last but not least, we
abstract from triggers and workflow attributes because it allows us to use classical
Petri nets instead of high-level Petri nets. From an analysis point of view, the clas-
sical Petri net is preferable because of the availability of efficient algorithms and

35

powerful analysis tools.

time_out_1

c1 c3

processing_1

i archive o
register
time_out_2

c2 c4

processing_2

Figure 22: A sound WF-net to illustrate the fairness assumption.

Definition 7 states the requirements to guarantee that it is possible to terminate,
i.e., staring in state i it is always possible to reach the final state o. Consider for
example the WF-net shown in Figure 22. From any state reachable from state i,
there is a firing sequence that leads to state o. However, this does not guarantee
that the firing sequence will occur. For example, it is possible that always one of
the time-outs occurs before the task archive occurs. Therefore, we assume strong
fairness (cf. [Val87, Mur89]). This means that if we consider a arbitrary infinite
firing sequence of the extended net (PN , see Figure 23), each transition occurs in-
finitely often. (In the extended net an extra transition t is added which connects o
and i, thus making the net cyclic.) Strong fairness corresponds to the probablistic
interpretation of fairness, e.g., the enabling time of each task is negative exponen-
tially distributed, or enabled tasks are selected in random order (cf. [MBea95]).
Assuming soundness and strong fairness, it is guaranteed that each case will end
up in place o eventually. A weaker form of fairness is often not sufficient. Consider
for example the following notion of fairness: a transition that is enabled infinitely
often, will fire eventually. If we assume this notion of fairness, it is not guaran-
teed that state o will be reached in Figure 22. If the tasks processing 1, time out 1,
processing 2, and time out 2 fire alternately, then task archive will never become
enabled and, in spite of the weak-fairness assumption, termination is not guaran-
teed. However, it is reasonable to assume strong fairness in the context of workflow
management. Moreover, it is quite easy to detect behavior which violates the as-
sumption of strong fairness, e.g., count the number of times each task is executed
for a specific case.

36

5.3 A necessary and sufficient condition for soundness
Given a WF-net PN = (P T F ), we want to decide whether PN is sound. For
this purpose we define an extended net PN = (P T F ). PN is the Petri net
obtained by adding an extra transition t which connects o and i. The extended
Petri net PN = (P T F ) is defined as follows: P = P , T = T ft g, and
F = F fho t i ht iig. Figure 23 illustrates the relation between PN and PN .
The extended net PN can be used to facilitate the verification of the soundness
property. The following theorem shows that the extended net allows for the for-
mulation of the soundness property in terms of well-known Petri net properties.

*
t

PN o
i

Figure 23: PN =( PT ft g F fho t i ht iig).

Theorem 1 A WF-net PN is sound if and only if (PN i) is live and bounded.
Proof.
See [Aal97] or [Aal96a].

This theorem shows that standard Petri-net-based analysis techniques can be used
to verify soundness. Consider for example the workflow process definition shown
in Figure 15. We can use one of the many standard Petri-net-based analysis tools to
verify that the extended net is live and bounded. Therefore, the workflow process
specified in Figure 15 is guaranteed to behave properly (cf. Definition 7). Theo-
rem 1 is an extension of the results presented in [Aal95, SH95]. In [Aal95] we re-
strict ourselves to free-choice WF-nets. In free-choice Petri nets it is not allowed to
mix choice and synchronization (see Definition 8). Independently, Straub and Hur-
tado [SH95] found necessary and sufficient conditions for the soundness of COPA
nets. (COPA nets correspond to a subclass of free-choice Petri nets.)

5.4 Structural characterizations of soundness
Theorem 1 gives a useful characterization of the quality of a workflow process def-
inition. However, there are a number of problems:

37

For a complex WF-net it may be intractable to decide soundness. For arbi-
trary WF-nets soundness is decidable but also expensive in terms of time and
space complexity. If fact, the problem of deciding liveness and boundedness
is EXPSPACE-hard (cf. [CEP93]).
Soundness is a minimal requirement. Readability and maintainability issues
are not addressed by Theorem 1.
Theorem 1 does not show how a non-sound WF-net should be modified, i.e.,
it does not identify constructs which invalidate the soundness property.
These problems stem from the fact that the definition of soundness relates to the
dynamics of a WF-net while the workflow designer is concerned with the static
structure of the WF-net. Therefore, it is interesting to investigate structural charac-
terizations of sound WF-nets. For this purpose we introduce three interesting sub-
classes of WF-nets: free-choice WF-nets, well-structured WF-nets, and S-coverable
WF-nets.

5.4.1 Free-choice WF-nets
Most of the workflow management systems available at the moment, abstract from
states between tasks, i.e., states are not represented explicitly. These workflow
management systems use building blocks such as the AND-split, AND-join, OR-
split and OR-join to specify workflow procedures. The AND-split and the AND-
join are used for parallel routing. The OR-split and the OR-join are used for con-
ditional routing. Because these systems abstract from states, every choice is made
inside an OR-split building block. If we model an OR-split in terms of a Petri net,
the OR-split corresponds to a number of transitions sharing the same set of input
places (see Figure 21). This means that for these workflow management systems,
a workflow procedure corresponds to a free-choice Petri net.

Definition 8 (Free-choice) A Petri net is a free-choice Petri net iff for every two
transitions t1 and t2 , t1 t2 6= implies t1 = t2.

It is easy to see that a process definition composed out of AND-splits, AND-joins,
OR-splits and OR-joins is free-choice ([Aal97]). If two transitions t1 and t2 share
an input place ( t1 t2 6= ), then they are part of an OR-split, i.e., a ‘free choice’
between a number of alternatives. Therefore, the sets of input places of t1 and t2
should match ( t1 = t2). Figure 20 shows a free-choice WF-net. The WF-net
shown in Figure 15 is not free-choice: archive and process complaint share an in-
put place but the two corresponding input sets differ.

We have evaluated many workflow management systems and only a few of these

38

systems (e.g. COSA, INCOME, and LEU) allow for a construction which is com-
parable to a non-free choice WF-net. Therefore, it makes sense to consider free-
choice Petri nets. Clearly, parallelism, sequential routing, conditional routing and
iteration can be modeled without violating the free-choice property. Another rea-
son for restricting WF-nets to free-choice Petri nets is the following. If we allow
non-free-choice Petri nets, then the choice between conflicting tasks may be influ-
enced by the order in which the preceding tasks are executed. The routing of a case
should be independent of the order in which tasks are executed. A situation where
the free-choice property is violated is often a mixture of parallelism and choice.
Figure 24 shows such a situation. Firing transition t1 introduces parallelism. Al-
though there is no real choice between t2 and t5 (t5 is not enabled), the parallel
execution of t2 and t3 results in a situation where t5 is not allowed to occur. How-
ever, if the execution of t2 is delayed until t3 has been executed, then there is a
real choice between t2 and t5. In our opinion parallelism itself should be sepa-
rated from the choice between two or more alternatives. Therefore, we consider
the non-free-choice construct shown in Figure 24 to be improper. In literature, the
term confusion is often used to refer to the situation shown in Figure 24.

t2 t4
c1 c3
t1
i o
t3 t5
c2 c4

Figure 24: A non-free-choice WF-net containing a mixture of parallelism and
choice.

Free-choice Petri nets have been studied extensively (cf. [Bes87, DE95, Des92,
Esp90, Hac72]) because they seem to be a good compromise between expressive
power and analyzability. It is a class of Petri nets for which strong theoretical re-
sults and efficient analysis techniques exist. For example, the well-known Rank
Theorem ([DE95]) allows us to formulate the following corollary.

Corollary 1 A free-choice WF-net can be checked for soundness in polynomial
time.

Proof.
See [Aal96a].

Corollary 1 shows that, for free-choice nets, there are efficient algorithms to decide
soundness. It can also be shown that sound free-choice WF-nets are safe ([Aal96a]).

39

Although most workflow management systems only allow for free-choice work-
flows, free-choice WF-nets are not a completely satisfactory structural characteri-
zation of ‘good’ workflows. On the one hand, there are non-free-choice WF-nets
which correspond to sensible workflows (cf. Figure 15). On the other hand there
are sound free-choice WF-nets which make no sense. Nevertheless, the free-choice
property is a desirable property. If one can model a workflow as a free-choice WF-
net, one should do so. A workflow specification based on a free-choice WF-net can
be enacted by most workflow systems. Moreover, a free-choice WF-net allows for
efficient analysis techniques and is easy to understand. Non-free-choice constructs
such as the construct shown in Figure 24 are a potential source of anomalous be-
havior (e.g. deadlock) which is difficult to trace.

5.4.2 Well-structured WF-nets
Another approach to obtain a structural characterization of ‘good’ workflows, is
to balance AND/OR-splits and AND/OR-joins. Clearly, two parallel flows initi-
ated by an AND-split, should not be joined by an OR-join. Two alternative flows
created via an OR-split, should not be synchronized by an AND-join. As shown in
Figure 25, an AND-split should be complemented by an AND-join and an OR-split
should be complemented by an OR-join.

AND-split AND-join AND-split OR-join

OR-split OR-join OR-split AND-join

Figure 25: Good and bad constructions.

One of the deficiencies of the WF-net shown in Figure 20 is the fact that the AND-
split register is complemented by the OR-join c3 or the OR-join o. To formalize
the concept illustrated in Figure 25 we give the following definition.

Definition 9 (Well-handled, well-structured) A Petri net PN is well-handled iff
for any pair of nodes x and y such that one of the nodes is a place and the other
a transition and for any pair of elementary paths C1 and C2 leading from x to y ,
(C1 ) (C2 ) = fx y g ) C1 = C2. A WF-net PN is well-structured iff the
extended net PN is well-handled.

40

time_out

c5

c1 send_questionnaire c3 process_questionnaire

i evaluate o
register archive

c2 c6

c7 check_processing

process_complaint c8

Figure 26: A workflow process definition which is not well-structured.

Consider for example the alternative complaints handling process shown in Fig-
ure 26. The WF-net is not well-structured because the AND-split register is com-
plemented by the OR-join c6: there are two disjunct paths leading from register to
c6, one via c2 and evaluate, and one via c1, send questionnaire, c3, process quest-
ionnaire, c5, process complaint, c8 and check processing. These two paths high-
light the fact that the workflow process shown in Figure 26 is not sound. If task
evaluate puts a token in c6, then a token gets trapped in the second path (e.g. in
place c5). If the arc from c5 to process complaint is replaced by an arc from c5
to archive, then the AND-split register is complemented by the AND-join archive
and the WF-net is sound.
Figure 20 shows another example of a WF-net that is not well-structured. The WF-
net is not well-structured because AND-split register is complemented by c3.
c4

t2 t4

c1

t1 t3 t5

i c2 c3 o

Figure 27: A well-structured WF-net.

Figure 27 shows a typical example of a well-structured WF-net which is not free-
choice. The WF-net shown in Figure 22 is another example of well-structured net

41

which is not free-choice. Although both WF-nets are not free-choice, it is possible
to verify soundness for such a WF-net very efficiently.

Corollary 2 A well-structured WF-net can be checked for soundness in polyno-
mial time.

Proof.
See [Aal96a]. The proof uses the results presented in [ES90] and [BCD95].

Well-structured WF-nets and free-choice WF-nets have similar properties. In both
cases soundness can be verified very efficiently and soundness implies safeness.
In spite of these similarities, there are sound well-structured WF-nets which are
not free-choice (Figure 27) and there are sound free-choice WF-nets which are not
well-structured. In fact, it is possible to have a sound WF-net which is neither free-
choice nor well-structured (Figures 15 and 24).

5.4.3 S-coverable WF-nets
What about the sound WF-nets shown in Figure 15 and Figure 24? The WF-net
shown in Figure 24 can be transformed into a free-choice well-structured WF-net
by separating choice and parallelism. The WF-net shown in Figure 15 cannot be
transformed into a free-choice or well-structured WF-net without yielding a much
more complex WF-net. Place c5 acts as some kind of milestone which is tested by
the task process complaint. Traditional workflow management systems which do
not make the state of the case explicit, are not able to handle the workflow speci-
fied by Figure 15. Only workflow management systems such as COSA ([SL96])
have the capability to enact such a state-based workflow. Nevertheless, it is in-
teresting to consider generalizations of free-choice and well-structured WF-nets:
S-coverable WF-nets can be seen as such a generalization.

Definition 10 (S-coverable) A WF-net PN is S-coverable iff the extended net PN
=( P T F ) satisfies the following property. For each place p there is subnet PNs =
(Ps Ts Fs ) such that: p 2 Ps , Ps P , Ts T , Fs F , PN s is strongly con-
nected, PN s is a state machine (i.e. each transition in PN s has one input and one
output arc), and for every q 2 Ps and t 2 T : (q t) 2 F ) (q t) 2 Fs and
(t q ) 2 F ) (t q ) 2 Fs .

This definition corresponds to the definition given in [DE95]. A subnet PN s which
satisfies the requirements stated in Definition 10 is called an S-component. PN s
is a strongly connected state machine such that for every place q : if q is an input
(output) place of a transition t in PN , then q is also an input (output) place of t in
PN s.
42

The WF-nets shown in Figure 15 and Figure 24 are S-coverable. The WF-net shown
in Figure 26 is not S-coverable because c5 is not in any S-component. The fol-
lowing theorem shows that a S-coverability is a generalization of the free-choice
property and well-structuredness.

Theorem 2 A sound free-choice WF-net is S-coverable. A sound well-structured
WF-net is S-coverable.

Proof.
See [Aal96a].

All the sound WF-nets presented in this paper are S-coverable. Every S-coverable
WF-net is safe. The two WF-nets which are not sound, see Figure 26 and Fig-
ure 20, are not S-coverable. These examples show that there is a high correlation
between S-coverability and soundness. It seems that S-coverability is one of the
basic requirements any workflow process definition should satisfy. From a for-
mal point of view, it is possible to construct WF-nets which are sound but not S-
coverable. Typically, these nets contain places which do not restrict the firing of a
transition, but which are not in any S-component. (See for example Figure 65 in
[Rei85].) From a practical point of view, these WF-nets are to be avoided. WF-nets
which are not S-coverable are difficult to interpret because the structural and dy-
namical properties do not match. For example, these nets can be live and bounded
but not structurally bounded. There is no practical need for using constructs which
violate the S-coverability property. Therefore, we consider S-coverability to be a
basic requirement any WF-net should satisfy.

S-coverability can be verified in polynomial time. Unfortunately, in general it is
not possible to verify soundness of an S-coverable WF-net in polynomial time. The
complexity of deciding soundness for an S-coverable WF-net is PSPACE-complete.
For most applications this is not a real problem. In most cases the number of tasks
in one workflow process definition is less than 100 and the number of states is less
than 200.000. Tools using standard techniques such as the construction of the co-
verability graph have no problems in coping with these workflow process defini-
tions.

5.5 Summary
The three structural characterizations (free-choice, well-structured, and S-coverable)
turn out to be very useful for the analysis of workflow process definitions. S-cover-
ability is a desirable property any workflow definition should satisfy. Constructs
violating S-coverability can be detected easily and tools can be build to help the

43

designer to construct an S-coverable WF-net. S-coverability is a generalization of
well-structuredness and the free-choice property (Theorem 2). Both well-struc-
turedness and the free-choice property also correspond to desirable properties of a
workflow. A WF-net satisfying at least one one of these two properties can be an-
alyzed very efficiently. However, we have shown that there are workflows that are
not free-choice and not well-structured. Consider for example Figure 15. The fact
that task process complaint tests whether there is a token in c5 prevents the WF-net
from being free-choice or well-structured. Although this is a very sensible work-
flow, most workflow management systems do not support such an advanced rout-
ing construct. Even if one is able to use state-based workflows (e.g. COSA) allow-
ing for constructs which violate well-structuredness and the free-choice property,
then the structural characterizations are still useful. If a WF-net is not free-choice
or not well-structured, one should locate the source which violates one of these
properties and check whether it is really necessary to use a non-free-choice or a
non-well-structured construct. If the non-free-choice or non-well-structured con-
struct is really necessary, then the correctness of the construct should be double-
checked, because it is a potential source of errors.

6 Toolset
Workflow management is a very rewarding application domain for Petri nets. On
the one hand, Petri nets allow for the design of complex workflows using advanced
routing constructs. On the other hand, powerful analysis techniques can be used to
verify the correctness of a workflow process definition. Unfortunately, most work-
flow management systems are not based on Petri nets. There are just a few products
which use Petri nets as a design language, e.g., COSA (Software Ley/COSA So-
lutions, Pullheim, Germany), INCOME (Promatis, Karlsbad, Germany), and LEU
(Vebacom, Bochum, Germany).

We have a lot of practical experience with the application of COSA. COSA is one
of the leading products at the Dutch workflow market. The COSA workflow man-
agement system consists of a number of components:

COSA Network Editor (CONE)
CONE is a tool to design workflow process definitions. Figure 28 shows a
window of CONE.

COSA User Editor (COUE)
COUE is used for the classification of resources in terms of roles and orga-
nizational units.

44

Figure 28: A COSA workflow process definition made with CONE.

COSA Simulator (COSI)
COSI is a primitive simulation tool which can be used to validate workflow
process definitions.

COSA Runtime Service (CORS)
CORS is a workflow enactment service which consists of one or more work-
flow engines.

COSA MemoBox (COMB)
COMB is a workflow client application (in-basket) which offers work items
to the end user.

COSA Networkstatus Displayer (COND)
COND is an extension of COMB which allows the end user to see the work-
flow state of a case.

COSA Administrator (COAD)
COAD is an administration and monitoring tool which can be used to handle
abnormalities, execute changes, detect problems, and collect management
information.

COSA is based on Petri nets: CONE uses Petri nets as a design language, COSI
and COND visualize the workflow in terms of a Petri net, and CORS uses the firing
rule to enact the workflow.

45

COSA allows for the modeling and enactment of complex workflow processes which
use advanced routing constructs. However, COSA does not support verification, it
does not allow for detailed simulation, and it is difficult to use for users which are
just interested in business process modeling. We use COSA in combination with
three other products to overcome these problems: Protos, ExSpect, and Woflan.
These products can interface with each other. Figure 29 shows the relations be-
tween COSA, Protos, ExSpect, and Woflan.

Woflan
(EUT)
verification
Protos COSA
(Pallas Athena) (Software-Ley)

(re)design enactment
ExSpect
(Bakkenist/EUT)

(performance) analysis

Figure 29: An integrated set of tools for the design, analysis and enactment of
workflows.

Protos (Pallas Athena, Plasmolen, The Netherlands) is a so-called BPR-tool. Pro-
tos supports Business Process Reengineering (BPR) efforts and can be used to mo-
del and analyze business processes ([Pal97]). The tool is very easy to use and
is based on Petri nets. To facilitate the modeling of simple workflows by users
not familiar with Petri nets, it is possible to abstract from states. Another exam-
ple of a BPR-tool based on Petri nets is Structware/BusinessSpecs (IvyTeam, Zug,
Switzerland). This tool can be used to model and simulate business processes which
can be exported to Staffware (Staffware, London, United Kingdom). Staffware is
one of the leading workflow products in the world.

ExSpect (Bakkenist Management Consultants, Diemen, The Netherlands) can be
used to model and simulate processes modeled in terms of high-level Petri nets
([Bak96]). (The first versions of ExSpect have been developed by members of
the department of Mathematics and Computing Science of Eindhoven University
of Technology.) Workflow processes modeled with Protos or COSA can be im-
ported into ExSpect. During the simulation of a workflow process with ExSpect,
the workflow is animated and key performance indicators (e.g. average throughput
time and occupation rate) are measured.

46

Figure 30: One of the many analysis windows of Woflan.

Woflan (Eindhoven University of Technology, Eindhoven, The Netherlands) is a
Petri-net-based workflow analyzer ([HVA97, AHV97]). Woflan (WOrkFLow AN-
alyzer) can be used to verify the correctness of a workflow. The tool is workflow
management system independent, i.e., a number of import functions to download
workflow scripts in Woflan (e.g. from COSA and Protos) are provided. Woflan
uses standard Petri-net-based analysis techniques. However, the analysis results
are presented in such a manner that end-users are able to understand the output of
Woflan. Moreover, Woflan guides the end-user in correcting an erroneous work-
flow. One of the central issues which is analyzed by Woflan is the soundness prop-
erty. Deciding whether the workflow definition is sound is not sufficient. In many
cases more requirements need to be satisfied. Moreover, if the workflow definition
is not sound, then the user should be guided in detecting the source of the error
and support should be given to repair the error. This is why Woflan offers a large
selection of analysis methods including the methods discussed in this paper. For
example, Woflan detects constructs which violate the free-choice property, well-
structuredness or S-coverability, calculates invariants, detects unbounded places,
and reports dead transitions.

47

7 Conclusion
In this paper we discussed the application of Petri nets to the workflow domain.
Workflow management turns out to be an application domain which could benefit
from the features of Petri nets. There are at least three good reasons for using Petri
nets for workflow modeling and analysis ([Aal96b]):

Formal semantics despite the graphical nature
On the one hand, Petri nets are a graphical language which allows for the
modeling of the workflow primitives identified by the WfMC. On the other
hand, the semantics of Petri nets (including most of the extensions) have
been defined formally. Many of today’s available workflow management
systems provide ad-hoc constructs to model workflow procedures. More-
over, there are workflow management systems that impose restrictions on
the workflow primitives shown in Figure 12. Some workflow management
systems also provide exotic constructs whose semantics are not 100% clear.
Because of these problems it is better to use a well-established design lan-
guage with formal semantics.

State-based instead of event-based
In contrast with many other process modeling techniques, the state of case
can be modeled explicitly in a Petri net. Process modeling techniques rang-
ing from informal techniques such as dataflow diagrams to formal techniques
such as process algebra’s are event-based, i.e., transitions are modeled ex-
plicitly and the states between subsequent transitions are modeled implicitly.
Today’s workflow management systems are typically event-based, i.e., tasks
are modeled explicitly and states between subsequent tasks are suppressed.
The distinction between an event-based and a state-based description seems
to be very subtle, but examples in this paper (e.g. Figure 16) show that this
is of the utmost importance for workflow modeling. For example, in most
workflow management systems which abstract from states it is not possible
to use the implicit OR-split.

Abundance of analysis techniques
Petri nets are marked by the availability of many analysis techniques. Clearly,
this is a great asset in favor of a Petri nets. In this paper, we focused on the
verification of workflows. We have seen that Petri-net-based analysis tech-
niques can be used to determine the correctness of a workflow process def-
inition. The availability of these techniques illustrates that Petri-net theory
can be used to add powerful analysis capabilities to the next generation of
workflow management systems.

48

Today’s situation with respect to workflow management software is comparable
to the situation as regards to database management software in the early seven-
ties. In the beginning of the seventies most of the pioneers in the field of DBMSs
were using their own ad-hoc concepts. This situation of disorder and lack of con-
sensus resulted in an incomprehensive set of DBMSs. However, emerging stan-
dards such as the Relational Data Model [Cod70] and the Entity-Relationship Mo-
del [Che76] lead to a common formal basis for many DBMSs. As a result, the use
of these DBMSs boosted. There are many similarities between today’s workflow
management systems and the DBMSs of the early seventies. Despite the efforts
of the Workflow Management Coalition a real conceptual standard is missing. As
a result, many organizations are reluctant to use existing workflow management
software. In our opinion Petri nets constitute a good basis for standardization. We
have just given three solid reasons for using a Petri-net-based workflow manage-
ment system. Inspired by practical experiences, we have come to realize that many
of the features of the Petri net formalism are useful in the context of workflow man-
agement.

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