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CS 594 Software Engineering

CS 594 Software Engineering. Lecture 3 Dr. Thomas E. Potok potokte@ornl.gov 865-574-0834. Agenda. Review COCOMO PERT. AMI Update. 200 jobs per day AMI has received a quote from Acme Consulting of $40K to do the work in 2 months Ballpark price range for AMI is $20-$30K.

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CS 594 Software Engineering

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  1. CS 594 Software Engineering Lecture 3 Dr. Thomas E. Potok potokte@ornl.gov 865-574-0834 T. E. Potok - University of Tennessee

  2. Agenda • Review • COCOMO • PERT T. E. Potok - University of Tennessee

  3. AMI Update • 200 jobs per day • AMI has received a quote from Acme Consulting of $40K to do the work in 2 months • Ballpark price range for AMI is $20-$30K. T. E. Potok - University of Tennessee

  4. Linear Regression Where is an estimate of the mean of Y, and are numerical estimated of the parameters T. E. Potok - University of Tennessee

  5. Many early studies applied regression • Data gathered from multiple software project • Log-linear relationship found between project size and effort • Where PM are person-months, KLOC is thousands of lines of code T. E. Potok - University of Tennessee

  6. Derivation T. E. Potok - University of Tennessee

  7. Typical Effort Vs Project Size Curve T. E. Potok - University of Tennessee

  8. Constructive Cost Model (COCOMO) • Developed by Barry Boehm • Statistical model of software development effort and time. • Base on results from 63 projects completed at TRW. • Basic model is a log-linear regression model that fits the 63 projects • Productivity ranges: • 20 - 1250 LOC/PM T. E. Potok - University of Tennessee

  9. Basic COCOMO • Organic - small to medium size, familiar projects • Person-months=2.4(KLOC)1.05 • Development-time = 2.5(PM).38 • Semidetached - intermediate • Person-months=3.0(KLOC)1.12 • Development-time = 2.5(PM).35 • Embedded - ambitious, tightly constrained • Person-months=3.6(KLOC)1.20 • Development-time = 2.5(PM).32 T. E. Potok - University of Tennessee

  10. COCOMO Models T. E. Potok - University of Tennessee

  11. Cost Drivers • Product Attributes • Required Reliability • Database Size • Product Complexity • Computer Attributes • Execution Time Constraints • Main storage constraints • Virtual Machine Volatility • Computer turnaround time T. E. Potok - University of Tennessee

  12. More Cost Drivers • Personnel Attributes • Analyst Capability • Application Experience • Programmer Capability • Virtual Machine Experience • Programming Language Experience • Project Attributes • Modern Programming Practices • Use of Software Tools • Required Development Schedule T. E. Potok - University of Tennessee

  13. Example • Need to produce 10,000 LOC, 10 KLOC. • Small project, familiar development • Use organic model: • Person-months=2.4(10)1.05 =26.9 Person-months • Development-time = 2.5(26.9).38 =8.7 Months • Average People = 26.9 PM/8.7 Months = 3 People • Linear model 3 people would take 16.5 months, at 50 person-months T. E. Potok - University of Tennessee

  14. Example • We also know that the design experience is low • Analyst, - 1.19 • application, - 1.13 • programmer experience is low. - 1.17 • Yet the programming experience is high - .95 • Adjustment factor 1.19*1.13*1.17*.95 = 1.49 • PM = 26.9*1.49 = 40 Person-months • Development time = 10.2 Months • People = 3.9 People T. E. Potok - University of Tennessee

  15. Drawbacks • COCOMO has to be calibrated to your environment. • Very sensitive to change. • Over a person-year difference in a 10 KLOC project with minor adjustments • Broad brush model that can generate significant errors T. E. Potok - University of Tennessee

  16. COCOMO 2.0 • Includes • COTS and reusable software • Degree of understanding of requirements and architectures • Schedule constraints • Project size • Required reliability • Three Types of models • Application Composition - Prototyping or RAD • Early Design - Alternative evaluation • Post-architecture - Detailed estimates T. E. Potok - University of Tennessee

  17. COCOMO Summary • Quick and easy to use • Provides a reasonable estimate • Needs to be calibrated • Results must be treated as ball park values unless substantial validation has been performed. T. E. Potok - University of Tennessee

  18. PERT • Project Evaluation and Review Technique • Developed for the Navy Polaris Missile Program • Directed Acyclic Graphs of project activities • Used for estimation and control of a project T. E. Potok - University of Tennessee

  19. Start project Gather requirements Document requirements Create design Document design Review design Create code Document code Define test cases Test code Demonstrate Finish project Example To create our 10K program we need the following activities T. E. Potok - University of Tennessee

  20. PERT Example Test Case Start Req Design Review Code Test Demo Finish Doc Code Doc Design Doc Req T. E. Potok - University of Tennessee

  21. Duration Estimates T. E. Potok - University of Tennessee

  22. Critical Path Estimate T. E. Potok - University of Tennessee

  23. Completion Probability T. E. Potok - University of Tennessee

  24. Cumulative Completion Probability 80% Probability of Completion in 46 days T. E. Potok - University of Tennessee

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