Estimation

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  • Developed by L. Putman et al.
  • FSP: full-time software personnel
  • Estimation

    1. 1. Software Cost Estimation J. C. Huang Department of Computer Science University of Houston Houston, TX 77204-3010
    2. 2. On Precision It is the mark of an instructed mind to rest satisfied with the degree of precision which the nature of subject admits, and not to seek exactness when only an approximation of the truth is possible... -Aristotle©J. C. Huang 2005 Estimation Slide 2 of 44
    3. 3. An Observation Estimation of resources, cost, and schedule for a software development effort requires experience, access to good historical information, and the courage to commit to quantitative measures when qualitative data are all that exist.©J. C. Huang 2005 Estimation Slide 3 of 44
    4. 4. Another Observation Estimation for software project carries inherent risk because of uncertainty in project complexity, project size, and structure (of requirements and problem to be solved).©J. C. Huang 2005 Estimation Slide 4 of 44
    5. 5. Major FactorsMajor factors that influence software cost:• product size and complexity• programmer ability• available time• required reliability• level of technology©J. C. Huang 2005 Estimation Slide 5 of 44
    6. 6. Three Approaches Estimation can be done by using • experience and historical data • decomposition techniques • empirical models©J. C. Huang 2005 Estimation Slide 6 of 44
    7. 7. Decomposition Techniques To obtain an estimation, we can decompose the problem to be solved, or decompose the process.©J. C. Huang 2005 Estimation Slide 7 of 44
    8. 8. DecompositionDecomposition should be done in such a way that1. size can be properly estimated,2. cost or effort required for each component can be accurately estimated,3. the teams ability to handle the components is well known, and4. the estimated values will be relatively unaffected by changes to the requirements.©J. C. Huang 2005 Estimation Slide 8 of 44
    9. 9. Problem-Based Estimation 1. Based on the software scope, decompose the software into problem functions that can be estimated individually. 2. Estimate LOC or FP of each function. 3. Make optimistic (sopt), most likely (sm), and pessimistic (spess) estimates for each item. Then compute the expected value: EV = (sopt + 4 sm + spess)/6 4. Apply baseline productivity metrics to compute estimated cost or effort.©J. C. Huang 2005 Estimation Slide 9 of 44
    10. 10. Process-Based Estimation1. Decompose the process into a set of tasks or activities.2. Estimate the cost or effort required for each.©J. C. Huang 2005 Estimation Slide 10 of 44
    11. 11. Empirical Estimation Models• An estimation model provides empirically derived formulas to predict effort as a function of LOC or FP.• The data used to support these models are derived from a limited sample. Thus no model is appropriate for all classes of software.©J. C. Huang 2005 Estimation Slide 11 of 44
    12. 12. Structure of Estimation Model E = A + BXC where A, B, and C are empirically derived constants, E is the effort in person months, and X is the estimation variable, either in LOC or FP.©J. C. Huang 2005 Estimation Slide 12 of 44
    13. 13. LOC-based ModelWalston-Felix Model E = 5.2(KLOC)0.91Bailey-Basili Model E = 5.5+0.73(KLOC)1.16Boehm Model (simple) E = 3.2(KLOC)1.05Doty Model for KLOC > 9 E = 5.288(KLOC)1.047 ©J. C. Huang 2005 Estimation Slide 13 of 44
    14. 14. FP-based model Albrecht and Gaffney Model E = -13.39 + 0.0545(FP) Kemerer Model E = 60.62 + 7.728(FP)310-8 Matson, Barnett & Mellichamp Model E = 585.7 + 15.12(FP)©J. C. Huang 2005 Estimation Slide 14 of 44
    15. 15. COCOMOThe COnstructive COst MOdelIt is LOC-based.There are three models: basic, intermediate, and advanced.©J. C. Huang 2005 Estimation Slide 15 of 44
    16. 16. Three Classes of Software Project• Organic -- a relatively small simple project in which small teams with good application experience work to a set of less than rigid requirements.• Semi-detached -- an intermediate project in which teams with mixed experience must meet a mix of rigid and less than rigid requirements.• Embedded -- a project that must meet tight hardware, software, and operational constraints.©J. C. Huang 2005 Estimation Slide 16 of 44
    17. 17. The COCOMO (continued)The basic equations E = a(KLOC)b T = cEd where E is the effort required in person-months, T is the required development time in chronological months, KLOC is the estimated size of software in thousand lines of delivered source code. The constants a, b, c, and d are listed below:©J. C. Huang 2005 Estimation Slide 17 of 44
    18. 18. The COCOMO Model (continued) type of project a b c dorganic 2.4 1.05 2.5 0.38semi-detached 3.0 1.12 2.5 0.35embedded 3.6 1.20 2.5 0.32 ©J. C. Huang 2005 Estimation Slide 18 of 44
    19. 19. The COCOMO (continued) Effort equation for the intermediate model: E = a(KLOC)b(EAF) where EAF is the effort adjustment factor that ranges from 0.9 to 1.4, and constants a and b are©J. C. Huang 2005 Estimation Slide 19 of 44
    20. 20. The COCOMO (continued) type of project a b organic 3.2 1.05 semi-detached 3.0 1.12 embedded 2.8 1.20©J. C. Huang 2005 Estimation Slide 20 of 44
    21. 21. The Software EquationE = ((LOC)B0.333/P)3(1/t4)where E = effort in person-months t = project duration in months B = special skill factor ranging from 0.16 to 0.39 P = productivity parameter (ref. www.qsm.com)©J. C. Huang 2005 Estimation Slide 21 of 44
    22. 22. The Software EquationE = ((LOC)B0.333/P)3(1/t4)where E= effort in person-months t= project duration in months B= special skill factor ranging from 0.16 to 0.39 P = productivity parameter that reflects • overall process maturity and management practices • the extent to which good SE practices are used • the level of programming language used • the state of software environment • the skill and experience of the software team • the complexity of the application©J. C. Huang 2005 Estimation Slide 22 of 44
    23. 23. Major FactorsMajor factors that influence software cost:• product size and complexity• programmer ability• available time• required reliability• level of technology©J. C. Huang 2005 Estimation Slide 23 of 44
    24. 24. Product ComplexityThree categories of products: Application programs: those developed in the environment by a language compiler, such as C++. Utility programs: those written to provide user processing environments and make sophisticated use of the operating system facilities. System programs: those interact directly with hardware, and often involve concurrent processing with time constraints. ©J. C. Huang 2005 Estimation Slide 24 of 44
    25. 25. Required Effort Given KDSI, thousand lines of deliverable code, Required programmer-months: application programs: PM = 2.4 x (KDSI)1.05 utility programs: PM = 3.0 x (KDSI)1.12 system programs: PM = 3.6 x (KDSI)1.20©J. C. Huang 2005 Estimation Slide 25 of 44
    26. 26. Required Development TimeRequired development time: application programs: TDev = 2.5 x (PM)0.38 utility programs: TDev = 2.5 X (PM)0.35 system programs: TDev = 2.5 x (PM)0.32©J. C. Huang 2005 Estimation Slide 26 of 44
    27. 27. Unit cost vs. size (assuming $5,000/PM) 80 sy stem 70 Dollars per line of source code 60 50 40 utility 30 20 application 10 0 1 1 10 2 100 1000 3 10000 4 Sof tware size in 1,000 lines of code©J. C. Huang 2005 Estimation Slide 27 of 44
    28. 28. Required development time vs. size 60 application 50 Required dev elopment time in months utility 40 sy stem 30 20 10 0 0 1 1 10 100 2 1000 3 10000 4 Sof tware size in 1,000 lines of source code©J. C. Huang 2005 Estimation Slide 28 of 44
    29. 29. Productivity vs. size Lines of code per prgrammer per day 0,03 30 0,02 20 application (11.8) utility 0,01 10 (5.8) sy stem (2.8) 0,000 0 0 1 1 10 100 2 1000 3 4 10000 Sof tware size in 1,000 lines of source code©J. C. Huang 2005 Estimation Slide 29 of 44
    30. 30. Major FactorsMajor factors that influence software cost:• product size and complexity• programmer ability• available time• required reliability• level of technology©J. C. Huang 2005 Estimation Slide 30 of 44
    31. 31. How programmers spend their time. Writing programs 13% Reading programs and manuals 16% Job communications 32% Personal 13% Miscellaneous 15% Training 6% Mail 5% Based on Bell Lab Study conducted in 1964 on 70 programmers©J. C. Huang 2005 Estimation Slide 31 of 44
    32. 32. Programmer’s Ability Variations in programmers abilities worst/best ratioperformance measure program #1 program # 2 debugging hours 28:1 26:1 CPU time 8:1 11:1 coding hours 16:1 25:1 program size 6:1 5:1 run time 5:1 13:1©J. C. Huang 2005 Estimation Slide 32 of 44
    33. 33. Programmer’s Ability (continued) By eliminating extreme performance in both directions, a variability of 5 to 1 in programmer productivity can be expected.©J. C. Huang 2005 Estimation Slide 33 of 44
    34. 34. Available Time Software projects require more total effort if development time is compressed or expanded from the optimal time.©J. C. Huang 2005 Estimation Slide 34 of 44
    35. 35. Available Time (continued) According to Putnam, a schedule compression of 0.86 will increase required staff by a factor of 1.82.©J. C. Huang 2005 Estimation Slide 35 of 44
    36. 36. Available Time (continued) It is commonly agreed that there is a limit beyond which a software project cannot reduce its schedule by adding more personnel and equipment. This limit occurs roughly at 75% of the normal schedule.©J. C. Huang 2005 Estimation Slide 36 of 44
    37. 37. COCOMO Effort MultipliersProduct attributes Required reliability 0.75 to 1.40 Data-base size 0.94 to 1.16 Product complexity 0.70 to 1.65©J. C. Huang 2005 Estimation Slide 37 of 44
    38. 38. COCOMO Effort Multipliers (continued)Computer attributes Execution time constraint 1.00 to 1.66 Main storage constraint 1.00 to 1.56 Virtual machine volatility 0.87 to 1.30 Computer turn-around time 0.87 to 1.15©J. C. Huang 2005 Estimation Slide 38 of 44
    39. 39. COCOMO Effort Multipliers (continued)Personnel attributes Analyst capability 1.46 to 0.71 Programmer capability 1.42 to 0.70 Applications experience 1.29 to 0.82 Virtual machine experience 1.21 to 0.90 Programming language experience 1.14 to 0.95©J. C. Huang 2005 Estimation Slide 39 of 44
    40. 40. COCOMO Effort Multipliers (continued)Project attributes Use of modern programming practices 1.24 to 0.82 Use of software tools 1.24 to 0.83 Required development schedule 1.23 to 1.00©J. C. Huang 2005 Estimation Slide 40 of 44
    41. 41. Staffing Level Estimation A software project typically starts with a small group of capable people to do planning and analysis, a larger, but still small group to do architectural design. The size of required personnel increases in each successive phase, peaks at the implementation and system testing phase, and decreases in the maintenance phase.©J. C. Huang 2005 Estimation Slide 41 of 44
    42. 42. Staffing-Level Estimation The personnel level of effort required throughout the life cycle of a software product can be approximated by the following equation, which describes a Rayleigh curve:©J. C. Huang 2005 Estimation Slide 42 of 44
    43. 43. Staffing-Level Estimation (continued) (0.15Tdev+0.7t)2 0.15Tdev+0.7t - FSP = PM( )e 0.5(Tdev)2 0.25(Tdev)2where FSP is the no. of full-time software personnel required at time t, PM is the estimated programmer-months for product development, excluding planning and analysis, and Tdev is the estimated development time. ©J. C. Huang 2005 Estimation Slide 43 of 44
    44. 44. Staffing-Level Estimation (continued)FSP Rayleigh curve t ©J. C. Huang 2005 Estimation Slide 44 of 44
    45. 45. Skills most lacking in entry level programmers• Express oneself clearly in English• Develop and validate software requirements and specifications• Work within applications area• Perform software maintenance• Perform economic analyses• Work with project management techniques• Work in group©J. C. Huang 2005 Estimation Slide 45 of 44

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