Software estimation

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Slides from software estimation session at C'Ville's 2010 beCamp.

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Software estimation

  1. 1. Coping with Software Estimation<br />Simeon H.K. Fitch<br />Mustard Seed Software, LLC<br />
  2. 2. What and Why<br />We have to do it<br />No one likes it<br />We’re always wrong<br />Real money and time is at stake<br />
  3. 3. References<br />A Review of Surveys on Software Effort Estimation<br />KjetilMoløkken and MagneJørgensen<br />Better sure than safe? Over-confidence in judgment based software development effort prediction intervals<br />MagneJørgensen, Karl HalvorTeigen, and KjetilMoløkken<br />
  4. 4. How<br />Expert based methods<br />Expert consultation<br />Intuition and experience<br />Analogy<br />Model based (Software Cost Models)<br />COCOMO<br />Use-Case-based estimation<br />FPA-metrics or other algorithm driven methods<br />Other<br />Price-to-win<br />Capacity related<br />Top-down<br />Bottom-up<br />
  5. 5. Results<br />Expert estimation most frequently used method<br />No evidence that the use of formal methods (on average) lead to more accurate estimate<br />Cost overrun more common than schedule overrun<br />Average cost overrun of 30-40%<br />
  6. 6. Results<br />Accuracy (according to one study)<br />If cost overrun (34%)<br />Over budget: 61%<br />Under budget: 10%<br />If schedule overrun (22%)<br />Completed after schedule: 65%<br />Completed before schedule: 4%<br />
  7. 7. Results<br />Prediction intervals (estimate min/max)<br />In one study, students provided better prediction intervals than “experts”.<br />“The software professional may feel a pressure to indicate high development skills through narrow prediction intervals”<br />
  8. 8. Blame<br />Cost overruns<br />Over-optimistic estimates<br />Changes in design or implementation<br />Schedule overruns<br />Optimistic planning<br />Frequent changes in specification<br />Frequent requests for changes by users<br />Users’ lack of understanding of their own requirements<br />Other (not just bad estimation)<br />
  9. 9. What do you do?<br />NASA<br />
  10. 10. What do you do?<br />MSS<br />Complexity measure (intuition)<br />Per developer conversion factor (complexity to time)<br />Confidence value [0..1]<br />
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