Chapter 3- Software Project Management(Reduced).ppt
- 2. Organization of this Lecture: ▪ Introduction to Project Planning ▪ Software Cost Estimation – Cost Estimation Models – Software Size Metrics – Empirical Estimation – Heuristic Estimation – COCOMO ▪ Summary 2
- 3. Introduction ▪ Many software projects fail: –due to faulty project management practices: ▪It is important to learn different aspects of software project management. 3
- 4. Introduction ▪ Goal of software project management: –enable a group of engineers to work efficiently towards successful completion of a software project. 4
- 5. Responsibility of Project Managers ▪ Project proposal writing, ▪ Project cost estimation, ▪ Scheduling, ▪ Project staffing, ▪ Project monitoring and control, ▪ Software configuration management, ▪ Risk management, ▪ Managerial report writing and presentations, etc. 5
- 6. Activities ▪ A project manager’s activities are varied. –can be broadly classified into: ▪project planning, ▪project monitoring and control activities. 6
- 7. Project Planning ▪ Once a project is found to be feasible, –project managers undertake project planning. ▪ Requires utmost care and attention - commitments to unrealistic time and resource estimates result in: –irritating delays. –customer dissatisfaction –adverse affect on team morale ▪ poor quality work –project failure. 7
- 8. Sliding Window Planning ▪ Involves project planning over several stages: –protects managers from making big commitments too early. –More information becomes available as project progresses. ▪Facilitates accurate planning 8
- 9. Project Planning Activities ▪ Estimation: Effort, cost, resource, and project duration ▪ Project scheduling ▪ Staff organization: staffing plans ▪ Risk handling: identification, analysis, and abatement procedures ▪ Miscellaneous plans: quality assurance plan, configuration management plan, etc. 9
- 10. SPMP Document ▪ After planning is complete: – Document the plans: –in a Software Project Management Plan(SPMP) document. 10
- 11. Organization of SPMP Document –Introduction: (Objectives, Major Functions, Performance Issues, Management andTechnical Constraints) –Project Estimates: (Historical Data, EstimationTechniques, Effort, Cost, and Project Duration Estimates) –Project Resources Plan: (People, Hardware and Software, Special Resources) –Schedules: (Work Breakdown Structure,Task Network, Gantt Chart Representation, PERT Chart Representation) –Risk Management Plan: (Risk Analysis, Risk Identification, Risk Estimation, Abatement Procedures) –ProjectTracking and Control Plan –Miscellaneous Plans: (ProcessTailoring, Quality Assurance) 11
- 12. Software Cost Estimation ▪ Determine size of the product. ▪ From the size estimate, –determine the effort needed. ▪ From the effort estimate, –determine project duration, and cost. 12
- 13. 13 Size Estimation Effort Estimation Cost Estimation Duration Estimation Staffing Estimation Scheduling Software Cost Estimation
- 14. Software Size Estimation ▪Three main approaches to estimation: –LOC (Line Of Code) –Function Point Metric –Feature Point Metric 14
- 15. Software Size Metrics ▪ LOC (Lines of Code): –Simplest and most widely used metric. –Comments and blank lines should not be counted. –Divides the problem into modules. –Each module into sub-modules and so,on until the LOC of the leaf level modules are small enough to be predicted. 15
- 16. Disadvantages of Using LOC ▪ Size can vary with coding style. ▪ Focuses on coding activity alone. ▪ Correlates poorly with quality and efficiency of code. ▪ Penalizes higher level programming languages, code reuse, etc. 16
- 17. Disadvantages of Using LOC (cont...) ▪ Measures lexical/textual complexity only. –does not address the issues of structural or logical complexity. ▪ Difficult to estimate LOC from problem description. –So not useful for project planning 17
- 18. Function Point Metric ▪ Proposed by Albrecht in early 80’s (1983): –Step 1 : compute the unadjusted function point using heuristic expression. –Step 2 : refine parameters. –Step 3 : Compute FP. 18
- 19. Function Point Metric ▪ Input: – A set of related inputs is counted as one input. ▪ Output: – A set of related outputs is counted as one output. ▪ Inquiries: – Each user query type is counted. ▪ Files: – Files are logically related data and thus can be data structures or physical files. ▪ Interface: – Data transfer to other systems. 19
- 20. Step 1: Compute UFP (Unadjusted Function Point) ▪ UFP = (number of inputs) * 4 + (number of outputs) * 5 + (number of inquiries) * 4 + (number of files) * 10 + (number of interfaces) * 7 20
- 21. Type Simple Average complex Input 3 4 6 Output 4 5 7 Inquiry 3 4 6 No. of files 7 10 15 No. of interfaces 5 7 10 21 Step 2: Refine Parameters
- 22. ▪ TCF = (0.65 + 0.01 * DI) , where DI is Degree of Influence andTCF isTechnical Complexity Factor. ▪ FP = UFP *TCF 22 Step 3: Compute FP
- 23. Degree Of Influence 23 0 = No Influence 1 = Incidental 2 = Moderate 3 = Average 4 = Significant 5 = Essential
- 24. Function Point Metric (CONT.) ▪Suffers from a major drawback: –the size of a function is considered to be independent of its complexity. ▪Extend function point metric: – Feature Point metric: –considers an extra parameter: ▪Algorithm Complexity. 24
- 25. Function Point Metric (CONT.) ▪ Proponents claim: –FP is language independent. –Size can be easily derived from problem description ▪ Opponents claim: –it is subjective --- Different people can come up with different estimates for the same problem. 25
- 26. Software Cost Estimation ▪Three main approaches to estimation: –Empirical –Heuristic –Analytical 26
- 27. Software Cost Estimation Techniques ▪ Empirical techniques: –an educated guess based on past experience. ▪ Heuristic techniques: –assume that the characteristics to be estimated can be expressed in terms of some mathematical expression. ▪ Analytical techniques: –derive the required results starting from certain simple assumptions. 27
- 28. Empirical Estimation Techniques ▪ Expert Judgement: –An euphemism for guess made by an expert. –Suffers from individual bias. ▪ Delphi Estimation: –overcomes some of the problems of expert judgement. 28
- 29. Expert judgement ▪Experts divide a software product into component units: –e.g. GUI, database module, data communication module, billing module, etc. ▪Add up the guesses for each of the components. 29
- 30. Delphi Estimation: ▪Team of Experts and a coordinator. ▪Experts carry out estimation independently: –mention the rationale behind their estimation. –coordinator notes down any extraordinary rationale: ▪circulates among experts. 30
- 31. Delphi Estimation: ▪Experts re-estimate. ▪Experts never meet each other – to discuss their viewpoints. 31
- 32. Heuristic Estimation Techniques ▪SingleVariable Model: – Parameter to be Estimated=C1(Estimated Characteristic)d1 A = b^2 ▪Multivariable Model: –Assumes that the parameter to be estimated depends on more than one characteristic. – Parameter to be Estimated=C1(Estimated Characteristic)d1+ C2(Estimated Characteristic)d2+… – A = b^2 + c^3 + d –Usually more accurate than single variable models. 32
- 33. COCOMO ▪COCOMO (COnstructive COst estimation MOdel) proposed by Boehm. ▪Divides software product developments into 3 categories: –Organic –Semidetached –Embedded 33
- 34. Elaboration of Product classes ▪ Organic: –Relatively small groups ▪working to develop well-understood applications. ▪ Semidetached: –Project team consists of a mixture of experienced and inexperienced staff. ▪ Embedded: –The software is strongly coupled to complex hardware, or real-time systems. 34
- 35. COCOMO Model (CONT.) ▪ For each of the three product categories: –From size estimation (in KLOC), Boehm provides equations to predict: ▪project duration in months ▪effort in programmer-months ▪ Boehm obtained these equations: –examined historical data collected from a large number of actual projects. 35
- 36. COCOMO Model (CONT.) ▪Software cost estimation is done through three stages: –Basic COCOMO, –Intermediate COCOMO, –Complete COCOMO. 36
- 37. Basic COCOMO Model (CONT.) ▪Gives only an approximate estimation: –Effort = a1 * (KLOC)^a2 PM –Tdev = b1 * (Effort)^b2 months ▪KLOC is the estimated kilo lines of source code, ▪a1,a2,b1,b2 are constants for different categories of software products, ▪Tdev is the estimated time to develop the software in months, ▪Effort estimation is obtained in terms of person months (PMs). 37
- 38. Development Effort Estimation ▪Organic : – Effort = 2.4 (KLOC)^1.05 PM ▪ Semi-detached: –Effort = 3.0(KLOC)^1.12 PM ▪ Embedded: –Effort = 3.6 (KLOC)^1.20PM 38
- 39. Development Time Estimation ▪Organic: –Tdev = 2.5 (Effort)^0.38 Months ▪Semi-detached: –Tdev = 2.5 (Effort)^0.35 Months ▪Embedded: –Tdev = 2.5 (Effort)^0.32 Months 39
- 40. Example ▪ The size of an organic software product has been estimated to be 32,000 lines of source code. Average salary of the engineers are 15,000 per month. ▪ Effort = 2.4*(32)^1.05 = 91 PM ▪ Nominal development time = 2.5*(91)0.38 = 14 months ▪ Cost = 91*15000 =13,65,000 40
- 41. Intermediate COCOMO ▪ Basic COCOMO model assumes –effort and development time depend on product size alone. ▪ However, several parameters affect effort and development time: ▪Reliability requirements ▪Availability of CASE tools and modern facilities to the developers ▪Size of data to be handled 41
- 42. Intermediate COCOMO ▪For accurate estimation, –the effect of all relevant parameters must be considered: –IntermediateCOCOMO model recognizes this fact: ▪refines the initial estimate obtained by the basic COCOMO by using a set of 15 cost drivers (multipliers). 42
- 43. Intermediate COCOMO (CONT.) ▪Rate different parameters on a scale of one to three: –Depending on these ratings, ▪multiply cost driver values with the estimate obtained using the basic COCOMO. 43
- 44. Intermediate COCOMO (CONT.) ▪ Cost driver classes: –Product: Inherent complexity of the product, reliability requirements of the product, etc. –Computer: Execution time, storage requirements, etc. –Personnel: Experience of personnel, etc. –Development Environment: Sophistication of the tools used for software development. 44
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- 47. Intermediate COCOMO ▪ Intermediate COCOMO equation: ▪ Effort=ai *(KLOC) ^bi*EAF Duration=ci (E)^di ▪ EAF- Effort Adjustment Factor 47
- 48. Example ▪ For a given project was estimated with a size of 300 KLOC. Calculate the Effort, Scheduled time for development by considering developer having very high application experience and very low experience in programming. 48
- 49. Answer ▪ Given the estimated size of the project is: 300 KLOC Developer having highly application experience: 0.82 (as per table) Developer having very low experience in programming: 1.14(as per table) ▪ EAF = 0.82*1.14 = 0.9348 ▪ Effort (E) = a*(KLOC)b *EAF = 3.0*(300)1.12 *0.9348 = 1668.07 PM ▪ Scheduled Time (D) = c*(E)d = 2.5*(1668.07)0.35 = 33.55 Months(M) 49
- 50. Shortcoming of basic and intermediate COCOMO models ▪ Both models: –consider a software product as a single homogeneous entity: –However, most large systems are made up of several smaller sub-systems. ▪Some sub-systems may be considered as organic type, some may be considered embedded, etc. ▪for some the reliability requirements may be high, and so on. 50
- 51. Complete COCOMO ▪Cost of each sub-system is estimated separately. ▪Costs of the sub-systems are added to obtain total cost. ▪Reduces the margin of error in the final estimate. 51
- 52. Complete COCOMO Example ▪ A Management Information System (MIS) for an organization having offices at several places across the country: –Database part (semi-detached) –Graphical User Interface (GUI) part (organic) –Communication part (embedded) ▪ Costs of the components are estimated separately: –summed up to give the overall cost of the system. 52
- 53. Summary ▪We discussed the broad responsibilities of the project manager: –Project planning –Project Monitoring and Control 53
- 54. Summary ▪ To estimate software cost: –Determine size of the product. –Using size estimate, ▪determine effort needed. –From the effort estimate, ▪determine project duration, and cost. 54
- 55. Summary (CONT.) ▪ Cost estimation techniques: –EmpiricalTechniques –HeuristicTechniques ▪ Empirical techniques: –based on systematic guesses by experts. ▪Expert Judgement ▪Delphi Estimation 55