Chapter 15 Projecting Defects( 缺陷预测 )

1. Chapter 15 Projecting Defects(缺陷预测)

2. outline • Analyze and use your defect data to help improve both planning accuracy and product quality. • Determine how best to prevent or find the defects you inject. • Control the quality of your work. 山东大学齐鲁软件学院

3. Defect rates • Defect injection rate typically range from about 50~250 defects per KLOC. • With Figure15.1 & 15.2 shown: • Defect density as a function of the years. • Some quality practices learn with experience. • defect levels are largely a matter of personal discipline. • After PSP training, engineers understood the numbers and types of defects. And then reduced their total defect injection rates. 山东大学齐鲁软件学院

4. Defect rates number are big! • Defect injection is a natural consequence of being human. • Average 100 defects/KLOC • About 50 defects/KLOC after PSP training. • So there are 50,000 defects in a 1,000,000 LOC program. • All of them must be found and fixed before delivery. 山东大学齐鲁软件学院

5. Using defect data • Gather defects data---help understanding the defects you inject to your program. • Design a personal checklist---for code reviewing to remove defects. • Establish a code standard---help to prevent defects injected in coding. • Then what’s our next step? what’s our final goal? 山东大学齐鲁软件学院

6. Using Defect Data • Task: Using historical defect data to make a reasonably good projections of the number of defects you will inject and remove in each phase of a programming project. • Advantage: By accurate estimates of defect levels, you can determine the likely quality of the program being developed. Then you can decide whether additional defect-removal steps are needed. • The final goal---defect-free programming, can not be achieved only by estimate, it should be approached by systematic work and step by step. • Defects collect, • Defect remove and prevent---code review and code standard, • Defect estimate. • Someday you will likely work on a project where defect-free work is essential! 山东大学齐鲁软件学院

7. Defect density • Defect density(Dd): the defects per thousand lines of code, measured by defects/KLOC. • Add up the total numbers of defects found. • Count the number of new and changed LOC • Calculate the defects per KLOC • Be sure not include library routine and copy part in counting LOC. 山东大学齐鲁软件学院

8. The calculation of Dd • Add up the total number of defects(D) found in all phases of the process, • Count the number(N) of new and changed LOC in the program, • Calculate the defects per KLOC as Dd = 1000*D/N. • For example, a 96 LOC program had a total 14 defects, then Dd = 1000*14/96 = 145.83 defects/KLOC. 山东大学齐鲁软件学院

9. Projecting Defects • Projecting defects • and then finally we achieve that we have ability to write a defect-free program • Then how to project defects in your program? • Plan Time • Plan project schedule • Then can defects be planned? 山东大学齐鲁软件学院

10. Difficulties of Projecting Defects Rates • Without experiences • Not be sure how some function or procedures works • Confused by language construct • Encounter new compiler or new programming enviroments • Solution: • Make more practices, to improve your skills and enrich your experience of programming • Gather and analyze defects data to continue improving. 山东大学齐鲁软件学院

11. Difficulties of Projecting Defects Rates • The process is not stable • The process is a new method and procedure to you, • defects injected, defects fix time are all fluctuating, especially defects fix may inject defect again. • Solution: • Improve the process by spending sufficient time on code reviewing to settle down the process. 山东大学齐鲁软件学院

12. Defect estimation • Using data of previously developed programs to calculate the Dplan • Ddplan= 1000*(D1+D2+…+Di)/(N1+N2+…+Ni) • Dplan = Nplan*Ddplan/1000， • or Dplan = Nplan*Dto date/Nto date. • The calculation of expected number of defects to be injected and removed in each phase. • Dphase = Dplanned total*Dto date %/100. 山东大学齐鲁软件学院

13. The updated project plan summary form and example • By using the project plan summary of a most previously developed program, make time plan and defect plan first. • Then by actual data, to complete the project plan summary for the new developed program. • Calculate the plan data • Calculate the To Date data • Entering the actual data 山东大学齐鲁软件学院

14. project plan summary 山东大学齐鲁软件学院

15. project plan summary 山东大学齐鲁软件学院

16. project plan summary 山东大学齐鲁软件学院

17. summary • Defect density. • Estimate defects injected. 山东大学齐鲁软件学院

18. Assignment • For the next program you write: • Determine the defects/KLOC rate and estimate the defects to be injected and removed by phase. • Inter these data in project plan summary. 山东大学齐鲁软件学院

19. Chapter 16The Economics of Defect Removal

20. outline • It’s trade-offs (平衡)between cost, schedule and quality; • It concerns three aspects: • The relative costs of removing defects during development; • The impact of any remaining defects on the customer; • The resulting customer support costs. • Hence, it’s a trade-off of risk and benefit. 山东大学齐鲁软件学院

21. The need for quality work • Defect-free software: no extra costs for defect removal, no risk for potential costs. But it’s always a final goal since the beginning of software development. • Defect removal costs a lot, especially in later phase. • Defect removal lowers benefit explicitly sometimes. • Defect removal does not bring benefit, but it can lower risk implied by remaining defects. 山东大学齐鲁软件学院

22. Defect-Removal problem • Defect-Removal is a software size and complexity related work. • The size and complexity of software system has increased ten times every ten years. • Laser printer driver: 20, 000 LOC ---1 million LOC; • More and more application, more and more complex; 山东大学齐鲁软件学院

23. Measurement of defect-removal • Measure defect-removal effectiveness • Defect-Removal Rate: number of defects removed in one hour. • Defect-Removal Yield(效益): Percentage of the defects found by a removal method. 山东大学齐鲁软件学院

24. Defect-Removal Time • Defect types • Requirement defect; • Design defect; • Coding injected defects • Defect-removal moment • Code reviewing; • Compiling; • Testing: Unit test and integrated test. • Varying from several minutes to several days • 250 engineers spent a full year on Microsoft NT system test finding and fixing 30,000 defects. This averages 16 hours per defect. 山东大学齐鲁软件学院

25. Defect injection and defect removal experience • The factors which affect the cost of defect-removal • Defect injection; • Defect removal experience • Figure 16.1 shows that bigger defect injection rate is made in coding than in design. • Figure 16.2 demonstrates that defect-removal in testing, code reviewing and compile, and in the phase of code reviewing, one can find more defects than in testing phase. 山东大学齐鲁软件学院

26. Defect Removal Savings • Compare the results of defect-removal with or without PSP. See table 16.1 in Page 214. • With PSP, software engineers have a great time savings. • With PSP, software product has less remaining defects (risks). 山东大学齐鲁软件学院

27. Defects/Hour on the PSP project plan summary • Comparison of defect injection/ removal rates of different phase • Def./Hour = 60*(To date defects injected/removed in one phase)/(To date Time in one phase (Min)). • See example in table 16.2 in page 216 山东大学齐鲁软件学院

28. Yield of defect removing • Def. Removed/Hour: Defects found rate in one phase • Also we would like to know how many defects were found and how many were missed in one defects removing phase---Yield • Moreover, • Process Yield = the percentage of the defects found before the first compile and test. • That is the percentage of the defects found in review phases (code review and design review), the percentage of the defects found initiatively（主动地）, not passively（被动地）. 山东大学齐鲁软件学院

29. Yield Calculation • Yield plan • Yield actual • Yield To Date • Yield = 100*(Defects removed before compile)/(Defects injected before compile). • See example of calculation in table 16.2 山东大学齐鲁软件学院

30. Improving Defect-Removal Rates • Focus on yield first. First objective must be to consistently achieve yields of 70% or more. • Do the code review before the first compile, and use the compiler to check the quality of your coding review. • Prone your code review checklist to improve your defect removal rates. • One definition of insanity is doing the same thing over and over and expecting a different result [Brown]. 山东大学齐鲁软件学院

31. Improving Defect-Removal Rates • gathering defects data • Calculating yield and defect-injection and defect-removal rates • Track these data in your programming practices. • One Objective of this doings: Making you conscious of the costs and consequences of defects, and then do the code review initiatively and efficiently. 山东大学齐鲁软件学院

32. Reducing Defect-Injected Rates • Record all your defects. • Be aware of defects, you will work more carefully and will reduce the number of defects of defects you inject. • Produce better design • Design process runs on the high level, more logically than coding, thus one makes less defects within the same time in design than in coding phase. • A complete and better-documented design will prevent defects injection in coding phase. • Frame guided • Save coding time 山东大学齐鲁软件学院

33. Reducing Defect-Injected Rates • Use better methods. • Objected oriented method • UML (Unified modeling language) and use case • Consistent coding convention. • Use better tools • Integrated programming environment • Visual interface of programming. 山东大学齐鲁软件学院

34. Summary • Defects are a principal cause of software problems. The remaining defects may lead severe consequences. • Defect fixing costs money and delays project schedules, and the defect fix times are unpredictable. So defect management is a economic issue. • Therefore, we need capture the key points in defects removing, improve defect removal rates and yield. • On the other hand, we need to reduce the defects injection rate by using better design, methods and tools. 山东大学齐鲁软件学院

35. Two measurements • Defects/Hour • Yield 山东大学齐鲁软件学院