Using Topic Models to Explain Software Defects
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1. The document discusses using topic models to study defects in software systems. 2. Topic models are used to analyze source code files and group them into topics, some of which are found to be more defect-prone than others. 3. Metrics related to topic membership are able to better explain post-release defects compared to traditional static and historical metrics. This suggests topics can help identify areas of code more likely to contain defects.
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Using Topic Models to Explain Software Defects
- 1. Explaining Software Defects Using Topic Models Tse-Hsun (Peter) Chen, Stephen W. Thomas, Meiyappan Nagappan, Ahmed E. Hassan
- 2. int readFile(String filePath){ fp = readFile(filePath) if fp == NULL return -1 else return fp } 2
- 3. int int manageMemory(int index){ readFile(String filePath){ if mem[index] is fp = not NULL{ readFile(filePath ) freeInd = if fp findFreeMemoryLoc() == NULL return -1 goto(freeInd) else } return fp } } 3
- 4. int int readFile(String manageMemory(int filePath){ index){ fp = if mem[index] is readFile(filePath not NULL{ ) freeInd = if fp == NULL findFreeMemoryLoc() return -1 goto(freeInd) else } return fp } } More Risky Concern 4
- 5. int int readFile(String manageMemory(int Can we use filePath){ index){ concerns to fp = if mem[index] is study readFile(filePath notdefects? NULL{ ) freeInd = if fp == NULL findFreeMemoryLoc() return -1 goto(freeInd) else } return fp } } More Risky Concern 5
- 6. Capturing Concerns Using Topic Models read file file path Topic 1 fp file read, file, path, path fp fp, file, index, Topics Models ind manage (LDA) Topic 2 memory manage, index mem memory, mem, free ind free, find, loc find free memory loc 6
- 7. How defect Can topics prone are explain software topics? defects? 7
- 8. Case Studies 3 versions of each system 0.4 - 8.8 MLOC 2.8 - 17 K files 1,300 ~ 6,500 post-release defects 8
- 9. How defect Can topics prone are explain software topics? defects? 9
- 10. If some topics are more defect- prone than others... We can allocate MORE testing resources on these topics! 10
- 11. If some topics are more defect- prone than others... We can allocate MORE testing resources on these topics! 11
- 12. Measuring Topic Defect-proneness T1 F1 T2 F2 T3 T4 F3 12
- 13. Measuring Topic Defect-proneness T1 F1 T2 F2 T3 T4 F3 13
- 14. Measuring Topic Defect-proneness T1 F1 T2 F2 T3 T4 F3 14
- 15. Measuring Topic Defect-proneness T1 F1 T2 F2 T3 T4 F3 15
- 16. Measuring Topic Defect-proneness T1 F1 T2 F2 T3 T4 F3 16
- 17. Measuring Topic Defect-proneness T1 F1 T2 F2 T3 T4 F3 17
- 18. Measuring Topic Defect-proneness T1 F1 T2 F2 T3 T4 F3 18
- 19. Measuring Topic Defect-proneness T1 F1 T2 F2 T3 T4 F3 19
- 20. Measuring Topic Defect-proneness T1 F1 T2 F2 T3 T4 F3 20
- 21. What is Relationship Between Defects and Topics? 21
- 22. What is Relationship Between Defects and Topics? T3 T2 T1 T4 22
- 23. What is Relationship Between Defects and Topics? T3 T2 T1 T4 T3 T2 T1 T4 23
- 24. What is Relationship Between Defects and Topics? T3 T2 T1 T4 24
- 25. Few Topics are Defect-prone 25
- 26. Few Topics are Defect-prone Task, Eclipse, Eclipse Mylyn, Task ui, Core, Repository 26
- 27. Few Topics are Defect-prone Lower color, Task, Eclipse, Jface, Eclipse Mylyn, Comparison check Task ui, Core, Repository 27
- 28. How defect Can topics prone are explain software topics? defects? Few Topics are Defect-prone! 28
- 29. How defect Can topics prone are explain software topics? defects? Few Topics are Defect-prone! 29
- 30. Explaining Defects 30
- 31. Explaining Defects Static 31
- 32. Explaining Defects Static Lines of Code 32
- 33. Explaining Defects Static Lines of Code Historical 33
- 34. Explaining Defects Static Lines of Code Pre-release Defects Historical Code Churn 34
- 35. Explaining Defects Static Lines of Code Pre-release Defects Historical Code Churn Topic Metrics Topics 35
- 36. Using Topics to Explain Defects T1 F1 T2 F2 T3 T4 F3 36
- 37. Using Topics to Explain Defects T1 F1 T2 F2 T3 T4 F3 37
- 38. Using Topics to Explain Defects T1 F1 T2 F2 T3 T4 F3 38
- 41. Explainability of Metrics Deviance Explained (D1) Static and AIC1 41
- 42. Explainability of Metrics Deviance Explained (D1) Static and AIC1 Topics 42
- 43. Explainability of Metrics Deviance Explained (D1) Static and AIC1 Topics Static 43
- 44. Explainability of Metrics Deviance Explained (D1) Static and AIC1 Topics Static D2 and AIC2 44
- 45. Explainability of Metrics Deviance Explained (D1) Static and AIC1 Topics Static D2 and AIC2 Improvement in Explainability = D2 – D1 and AIC2 – AIC1 45
- 46. More Topics More Defects in File %Avg. Imp. in D2 46
- 47. Topic Membership Metrics: Few Topics are Defect-prone T1 F1 T2 F2 T3 T4 F3 47
- 48. Dealing with Large # of Metrics 48
- 49. Dealing with Large # of Metrics Topic membership metrics may have as many as 500 variables! 49
- 50. Dealing with Large # of Metrics Topic membership metrics may have as many as 500 variables! Solution: Use PCA to reduce the number of metrics 50
- 51. Topic Memebership Metrics Explain Defects Even More % Avg. Imp. in AIC 51
- 52. How defect Can topics prone are explain software topics? defects? Few Topics are Defect-prone! YES! 52
- 53. Limitations 53
- 55. Limitations 1. Parameter Choices •Number of topics •Thresholds 55
- 56. Limitations 1. Parameter Choices •Number of topics •Thresholds 2. Used Baseline Metrics Static Historical 56
- 57. Limitations 1. Parameter Choices •Number of topics •Thresholds 2. Used Baseline Metrics Static Historical 3. Studied Three Subject Systems 57
- 58. Summary
- 59. Summary
- 60. Summary
- 61. Summary
- 62. Summary