software project management.lpu.slide.ansh.gupta
- 2. 2 Introduction Many software projects fail: due to faulty project management practices: It is important to learn different aspects of software project management.
- 3. 3 Introduction Goal of software project management: enable a group of engineers to work efficiently towards successful completion of a software project.
- 4. Project Manager A project manager is usually a experienced member of the team who especially works as the administrative leader of the team. 4
- 5. Software Project Management Complexities Invisibility :- Software remains invisible, until its development is complete and its operational. Changeability:- Frequent changes to the requirements and invisibility of software are two major factors. 5
- 6. Complexity :- Number of functions, data coupling. Uniqueness:- Every project is unique and associated with new features. Team oriented and Intellect-intensive work- 6
- 7. 7 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.
- 8. 8 Introduction A project manager’s activities are varied. can be broadly classified into: project planning, project monitoring and control activities.
- 9. 9 Project Planning Once a project is found to be feasible, project managers undertake project planning.
- 10. 10 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.
- 11. 11 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.
- 12. Project Monitoring The focus of project monitoring and control activities is to ensure that the software development proceeds as per plan. 12
- 13. Which of the following activity is undertaken immediately after feasibility study and before the requirement analysis and specification phase? A. Project Planning B. Project Monitoring C. Project Control D. Project Scheduling 13
- 14. 14 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
- 15. 15 SPMP Document After planning is complete: Document the plans: in a Software Project Management Plan(SPMP) document.
- 16. 16 Organization of SPMP Document Introduction (Objectives,Major Functions,Performance Issues,Management and Technical Constraints) Project Estimates (Historical Data,Estimation Techniques,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) Project Tracking and Control Plan Miscellaneous Plans(Process Tailoring,Quality Assurance)
- 17. 17 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.
- 19. 19 This activity is undertaken once the development activities start? A. Project Planning B. Project Monitoring and Control C. Project size estimation D. Project cost estimation
- 20. 20 Software Size Metrics LOC (Lines of Code): Simplest and most widely used metric. Comments and blank lines should not be counted.
- 21. 21 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.
- 22. 22 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
- 23. During project estimation, project manager estimates following A. project cost B. project duration C. project effort D. all of the above 23
- 24. 24 Function Point Metric Overcomes some of the shortcomings of the LOC metric Proposed by Albrecht in early 80's: FP=4 #inputs + 5 #Outputs + 4 #inquiries + 10 #files + 10 #interfaces Input: A set of related inputs is counted as one input.
- 25. 25 Function Point Metric 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.
- 26. 26 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.
- 27. 27 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.
- 28. 28 Project Estimation Technique Three main approaches to estimation: Empirical Heuristic Analytical
- 29. 29 Project Estimation Technique 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.
- 30. 30 Empirical Size 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.
- 31. 31 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.
- 32. 32 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.
- 33. 33 Delphi Estimation: Experts re-estimate. Experts never meet each other to discuss their viewpoints.
- 34. 34 Heuristic Estimation Techniques Single Variable Model: Parameter to be Estimated=C1(Estimated Characteristic)d1 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+… Usually more accurate than single variable models.
- 35. 35 COCOMO Model COCOMO (COnstructive COst MOdel) proposed by Boehm. Divides software product developments into 3 categories: Organic Semidetached Embedded
- 36. 36 COCOMO Product classes Roughly correspond to: application, utility and system programs respectively. Data processing and scientific programs are considered to be application programs. Compilers, linkers, editors, etc., are utility programs. Operating systems and real-time system programs, etc. are system programs.
- 37. 37 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.
- 38. 38 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.
- 39. 39 COCOMO Model(CONT.) Software cost estimation is done through three stages: Basic COCOMO, Intermediate COCOMO, Complete COCOMO.
- 40. 40 Basic COCOMO Model(CONT.) Gives only an approximate estimation: Effort = a1 (KLOC)a2 Tdev = b1 (Effort)b2 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).
- 41. 41 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
- 42. 42 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
- 43. 43 Basic COCOMO Model(CONT.) Effort is somewhat super-linear in problem size. Effort Size
- 44. 44 Basic COCOMO Model(CONT.) Development time sublinear function of product size. When product size increases two times, development time does not double. Time taken: almost same for all the three product categories. Size Dev. Time 60K 18 Months 14 Months 30K
- 45. 45 Basic COCOMO Model(CONT.) Development time does not increase linearly with product size: For larger products more parallel activities can be identified: can be carried out simultaneously by a number of engineers.
- 46. 46 Basic COCOMO Model(CONT.) Development time is roughly the same for all the three categories of products: For example, a 60 KLOC program can be developed in approximately 18 months regardless of whether it is of organic, semi- detached, or embedded type. There is more scope for parallel activities for system and application programs, than utility programs.
- 47. 47 Example The size of an organic software product has been estimated to be 32,000 lines of source code. Effort = 2.4*(32)1.05 = 91 PM Nominal development time = 2.5*(91)0.38 = 14 months
- 48. 48 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
- 49. 49 Intermediate COCOMO For accurate estimation, the effect of all relevant parameters must be considered: Intermediate COCOMO model recognizes this fact: refines the initial estimate obtained by the basic COCOMO by using a set of 15 cost drivers (multipliers).
- 50. 50 Intermediate COCOMO (CONT.) If modern programming practices are used, initial estimates are scaled downwards. If there are stringent reliability requirements on the product : initial estimate is scaled upwards.
- 51. 51 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.
- 52. 52 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.
- 53. 53 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.
- 54. 54 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.
- 55. 55 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.
- 56. 56 Halstead's Software Science An analytical technique to estimate: size, development effort, development time.
- 57. 57 Halstead's Software Science Halstead used a few primitive program parameters number of operators and operands Derived expressions for: over all program length, potential minimum volume actual volume, language level, effort, and development time.
- 58. 58 Staffing Level Estimation Number of personnel required during any development project: not constant. Norden in 1958 analyzed many R&D projects, and observed: Rayleigh curve represents the number of full-time personnel required at any time.
- 59. 59 Rayleigh Curve Rayleigh curve is specified by two parameters: td the time at which the curve reaches its maximum K the total area under the curve. L=f(K, td) Effort Time td Rayleigh Curve
- 60. 60 Putnam’s Work: In 1976, Putnam studied the problem of staffing of software projects: observed that the level of effort required in software development efforts has a similar envelope. found that the Rayleigh-Norden curve relates the number of delivered lines of code to effort and development time.
- 61. 61 Putnam’s Work(CONT.): Putnam analyzed a large number of army projects, and derived the expression: L=CkK1/3td4/3 K is the effort expended and L is the size in KLOC. td is the time to develop the software. Ck is the state of technology constant reflects factors that affect programmer productivity.
- 62. 62 Putnam’s Work(CONT.): Ck=2 for poor development environment no methodology, poor documentation, and review, etc. Ck=8 for good software development environment software engineering principles used Ck=11 for an excellent environment
- 63. 63 Rayleigh Curve Very small number of engineers are needed at the beginning of a project carry out planning and specification. As the project progresses: more detailed work is required, number of engineers slowly increases and reaches a peak.
- 64. 64 Rayleigh Curve Putnam observed that: the time at which the Rayleigh curve reaches its maximum value corresponds to system testing and product release. After system testing, the number of project staff falls till product installation and delivery.
- 65. 65 Rayleigh Curve From the Rayleigh curve observe that: approximately 40% of the area under the Rayleigh curve is to the left of td and 60% to the right.
- 66. 66 Effect of Schedule Change on Cost Using the Putnam's expression for L, K=L3/Ck3td4 Or, K=C1/td4 For the same product size, C1=L3/Ck3 is a constant. Or, K1/K2 = td24/td14
- 67. 67 Effect of Schedule Change on Cost(CONT.) Observe: a relatively small compression in delivery schedule can result in substantial penalty on human effort. Also, observe: benefits can be gained by using fewer people over a somewhat longer time span.
- 68. 68 Example If the estimated development time is 1 year, then in order to develop the product in 6 months, the total effort and hence the cost increases 16 times. In other words, the relationship between effort and the chronological delivery time is highly nonlinear.
- 69. 69 Effect of Schedule Change on Cost(CONT.) Putnam model indicates extreme penalty for schedule compression and extreme reward for expanding the schedule. Putnam estimation model works reasonably well for very large systems, but seriously overestimates the effort for medium and small systems.
- 70. 70 Effect of Schedule Change on Cost(CONT.) Boehm observed: “There is a limit beyond which the schedule of a software project cannot be reduced by buying any more personnel or equipment.” This limit occurs roughly at 75% of the nominal time estimate.
- 71. 71 Effect of Schedule Change on Cost(CONT.) If a project manager accepts a customer demand to compress the development time by more than 25% very unlikely to succeed. every project has only a limited amount of parallel activities sequential activities cannot be speeded up by hiring any number of additional engineers. many engineers have to sit idle.
- 72. 72 Jensen Model Jensen model is very similar to Putnam model. attempts to soften the effect of schedule compression on effort makes it applicable to smaller and medium sized projects.
- 73. 73 Jensen Model Jensen proposed the equation: L=CtetdK1/2 Where, Cte is the effective technology constant, td is the time to develop the software, and K is the effort needed to develop the software.
- 74. 74 Organization Structure Functional Organization: Engineers are organized into functional groups, e.g. specification, design, coding, testing, maintenance, etc. Engineers from functional groups get assigned to different projects
- 75. 75 Advantages of Functional Organization Specialization Ease of staffing Good documentation is produced different phases are carried out by different teams of engineers. Helps identify errors earlier.
- 76. 76 Project Organization Engineers get assigned to a project for the entire duration of the project Same set of engineers carry out all the phases Advantages: Engineers save time on learning details of every project. Leads to job rotation
- 77. 77 Team Structure Problems of different complexities and sizes require different team structures: Chief-programmer team Democratic team Mixed organization
- 78. 78 Democratic Teams Suitable for: small projects requiring less than five or six engineers research-oriented projects A manager provides administrative leadership: at different times different members of the group provide technical leadership.
- 79. 79 Democratic Teams Democratic organization provides higher morale and job satisfaction to the engineers therefore leads to less employee turnover. Suitable for less understood problems, a group of engineers can invent better solutions than a single individual.
- 80. 80 Democratic Teams Disadvantage: team members may waste a lot time arguing about trivial points: absence of any authority in the team.
- 81. 81 Chief Programmer Team A senior engineer provides technical leadership: partitions the task among the team members. verifies and integrates the products developed by the members.
- 82. 82 Chief Programmer Team Works well when the task is well understood also within the intellectual grasp of a single individual, importance of early completion outweighs other factors team morale, personal development, etc.
- 83. 83 Chief Programmer Team Chief programmer team is subject to single point failure: too much responsibility and authority is assigned to the chief programmer.
- 84. 84 Mixed Control Team Organization Draws upon ideas from both: democratic organization and chief-programmer team organization. Communication is limited to a small group that is most likely to benefit from it. Suitable for large organizations.
- 85. 85 Team Organization Chief Programmer team Democratic Team