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CS 562 Advanced SW Engineering

CS 562 Advanced SW Engineering. Lecture #6 Tuesday, May 18, 2004. Class Format for Today. Return Proposal #1 & Paper #2 Turn in Proposal #2 Questions Lecture #6: Chapter 4 – Calibration. Questions?. From last week’s class From the reading About the papers/project? Anything else?.

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CS 562 Advanced SW Engineering

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  1. CS 562Advanced SW Engineering Lecture #6 Tuesday, May 18, 2004 CS 562 - WPI

  2. Class Format for Today • Return Proposal #1 & Paper #2 • Turn in Proposal #2 • Questions • Lecture #6: • Chapter 4 – Calibration CS 562 - WPI

  3. Questions? • From last week’s class • From the reading • About the papers/project? • Anything else? CS 562 - WPI

  4. COCOMO IICalibration Boehm, et al Chapter 4 CS 562 - WPI

  5. Overview • Cost Estimation Models: • Models D, E and B • What are each of these? • Bayesian Calibration: • Takes the best from D & E to produce B • Which is a priori vs. a posteriori ? • What justification is given for this approach? CS 562 - WPI

  6. Modeling Methodology • 7 Modeling Steps in Figure 4.1, page 142 • What do they mean? • Operational Implications • How do they impact COCOMO II estimates? • What does it mean for the user? • What suggestions are given to deal with this complication? CS 562 - WPI

  7. Data Collection Approach • How does COCOMO II use consistency? • Data collection forms in Appendix C • 2000 candidate project data points filtered down to 161 • The Rosetta Stone • What is it? How is it used? • Review Table 4.1, page 146 • Differences between COCOMO 81 & COCOMO II CS 562 - WPI

  8. Model Building • Statistical Process: review Fig. 4.2, page 152 • Model problems vs. data problems • Observational vs. experimental data • What is Collinearity? • Review Eq. 4.1, page 153 and Eq. 4.2, page 154 • What do they mean? • Sampling of predictor region • Review Figs. 4.3-4.5, page 155 – Interpretation? • What are outliers & influential observations? CS 562 - WPI

  9. COCOMO II.1997 Calibration • What are Equations 4.3-4.5 about? (156,157) • Review Tables 4.7, 4.8 (158, 159) • Example of RUSE effort multiplier • How do Tables 49 a & b relate? (Page 160) • Why are regression coefficients negative? • What reasons are given? Explanation? • How is this issue resolved in COCOMO II? • See Table 4.10, page 163 CS 562 - WPI

  10. COCOMO II.2000 Calibration • What approach was used in the 2000 calibration that differs from the 1997 version? • Review Eqs. 4.6, 4.7, 4.8a & b (162-164) • Discuss the Delphi exercise • Purpose, approach, pros & cons • Discuss sample information • Purpose, approach • Review Figures 4.8 & 4.9, page 167 CS 562 - WPI

  11. Posterior Bayesian Update • How are the expert judgment (prior) data and sample data combined? • From the text: “ The resulting posterior precision will always be higher than the a priori precision or the sample data precision.” • Do you agree? Why / why not? • Review Figure 4.12, page 171 • Productivity ranges & variances CS 562 - WPI

  12. Validating Bayesian Approach • How do the authors determine that the Bayesian approach is valid? • Cross-validation (Section 4.5.2.2, p. 173) • Further validation (Sect. 4.5.2.3, p. 173-175) • Review Tables 4.15 (p. 173) & 4.16 (p. 174) • What results were obtained from the analysis? CS 562 - WPI

  13. Tailoring COCOMO II • Calibrating the model to existing project data • Multiplicative constant, A • See Equations 4.9, 4.10, p. 176 • Tables 4.17, 4.18 pages 176-177 • Baseline exponent, B • See Equation 4.11, page 179 • Table 4.22, p. 180 • Review Table 4.23, page 182 CS 562 - WPI

  14. More Tailoring • Consolidating or eliminating redundant parameters • Why bother? Examples? • Review Table 4.24, page 183 • Adding new significant cost drivers not already explicit in the model • Why bother? Examples? CS 562 - WPI

  15. For Next Time • Read remaining chapters in Brooks • Chapters 10 – 19 • Paper 3 due CS 562 - WPI

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