Improving Bug Location Using Binary Class Relationships

1. Improving Bug Location UsingImproving Bug Location Using
Binary Class RelationshipsBinary Class Relationships
SCAM 2012, Riva Del Garda, ItalySCAM 2012, Riva Del Garda, Italy
Nasir Ali, Aminata Sabane, Yann-Gaël Guéhéneuc, and Giuliano Antoniol

2. What is bug location?
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SOURCE CODE
Bug Report

3. How to find a buggy class(es)?
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4. Information Retrieval
Techniques
How to find a buggy class(es)?
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5. Problem with IR techniques
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Bug
LSI
Developer
IR Techniques
Searching!
“Bugs” Bunny

6. Our Conjecture!
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“Good” Developer
Send Email
Feature
Binary Class
Relationships (BCR)
Aggregation
Association
Use
Inheritance

7. Our Conjecture!
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Bug
LSI BCR
Developer
IR + BCR
Searching!

8. Proposed Approach
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BCR
IR
LIBCROOS

9. LInguistic (textual) and BCRs of Object
Oriented Systems (LIBCROOS)
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10. IR Engine
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• Input: Bug reports and source code
• Filter (#43@$)
• Stop words (the, is, an….)
• Stemmer (attachment, attached -> attach)
• IR Techniques
• Latent Semantic Indexing (LSI)
• Vector Space Model (VSM)
• Output
• Ranked list of linked bug reports and source code files based on
textual similarity
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11. Example of IR ranked list
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0.70
0.65
0.59
0.56
0.35
0.34
0.27
0.19
0.12
0.09
0.06

12. Relational Model
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• Input
• IR generated ranked list
• Source code OR binary classes
• Binary Class Relationships
• PADL model creator
• BCRs recovery
• BCRs filter
• Output
• Ranked list of linked bug reports and source code files based on
BCRs
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13. Example of BCRs
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IR
BCR
0.70
0.65
0.59
0.56
0.35
0.34
0.27
0.19
0.12
0.09
0.06

14. Ranker
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• Input
• IR generated ranked list
• Relational model generated ranked list
• Assign weights
• Assign weight to IR ranked list
• Assign weight to relational model generated ranked list
• Output
• New ranked list
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15. Example of Ranker
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IR
BCR

16. Case Study
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• Goal: Investigate the effectiveness of LIBCROOS in
improving the accuracy of VSM and LSI techniques
• Quality focus: Ability to decrease the rank of
buggy classes in ranked list produced by IR
techniques
• Context: Linking bug reports with source code of
four open-source programs, ……

17. Research Questions (RQs)
R01: Does LIBCROOS provide better accuracy, in
terms of ranking, than IR techniques?
R02: What are the important BCRs that help to
improve IR techniques accuracy more than
the others?
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18. Datasets
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Dataset Name Version Bug Reports Source Code
Files
Classes LOC
Rhino 1.5R4.1 41 111 111 94,078
Jabref 2.6 36 579 579 287,791
Lucene 3.1 89 434 434 111,117
muCommander 0.8.5 81 1,069 1,069 124,944

19. Case Studies Results (RQ1)
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Y axis shows buggy classes’ rank and X axis shows approaches

20. Case Studies Results
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21. RQs Answers
• R01: LIBCROOS helps to decrease the rank of culprit
classes and put culprit classes higher in the ranked
lists when compared to “traditional” IR techniques
alone.
R02: All BCRs helps to decrease the rank of culprit
classes. However, inheritance is the most important
BCR to decrease the ranking, then aggregation, use,
and association.
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