Integrated Impact Analysis for Managing Software Changes. Malcom Gethers, Bogdan Dit, Huzefa Kagdi, Denys Poshyvanyk
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1 Integrated Impact Analysis for Managing Software Changes Malcom Gethers, Bogdan Dit, Huzefa Kagdi, Denys Poshyvanyk
2 Change Impact Analysis Software change impact analysis aims at estimating the potentially impacted entities of a system due to a proposed change [Bohner and Arnold 96]
3 Impact Analysis (IA)
4 Impact Analysis (IA)
5 Impact Set Impact Analysis (IA)
6 Related Work Software change IA via Static and Dynamic Analysis [Law and Rothermel ICSE'03] [Orso et al. ESEC/ FSE'03] [Orso et al. ICSE'04] [Ren et al. OOPSLA'04] Software change IA via Information Retrieval [Canfora and Cerula MSR'06] [Hill et al. ASE'07] [Kagdi et al. WCRE'10] [Poshyvanyk et al. EMSE'09] Software change IA via Mining Software Repositories [Zimmermann et al. TSE'05] [Gall et al. ICSM'98] [Kagdi et al. WCRE'10] [Canfora and Cerula MSR'06]
7 Related Work Software change IA via Static and Dynamic Analysis [Law and Rothermel ICSE'03] [Orso et al. ESEC/ FSE'03] [Orso et al. ICSE'04] [Ren et al. OOPSLA'04]
8 Related Work Both relate to corpus processing Software change IA via Information Retrieval [Canfora and Cerula MSR'06] [Hill et al. ASE'07] [Kagdi et al. WCRE'10] [Poshyvanyk et al. EMSE'09]
9 Related Work Implement functionality related to request body handling Software change IA via Mining Software Repositories [Zimmermann et al. TSE'05] [Gall et al. ICSM'98] [Kagdi et al. WCRE'10] [Canfora and Cerula MSR'06]
10 Research Goal Develop a novel Impact Analysis (IA) approach that adapts to specific maintenance scenarios Information Retrieval (IR), Latent Semantic Indexing (LSI) Mining Software Repositories (MSR), Itemset Mining Run time information, execution traces
11 Research Goal Develop a novel Impact Analysis (IA) approach that adapts to specific maintenance scenarios Information Retrieval (IR), Latent Semantic Indexing (LSI) How can we integrate these information sources for IA? Mining Software Repositories (MSR), Itemset Mining Run time information, execution traces
12 Scenario-Driven Approach Default: Given a textual change request, an Information Retrieval (IR) (e.g., Latent Semantic Indexing) is used to estimate the impact set.
13 Scenario-Driven Approach Default: Given a textual change request, an Information Retrieval (IR) (e.g., Latent Semantic Indexing) is used to estimate the impact set. Scenario 1: User provides a Verified starting entity
14 Scenario-Driven Approach Default: Given a textual change request, an Information Retrieval (IR) (e.g., Latent Semantic Indexing) is used to estimate the impact set. Scenario 2: User provides an execution trace readanddispatch -- org.eclipse.swt.widgets.display checkdevice -- org.eclipse.swt.widgets.display isdisposed -- org.eclipse.swt.graphics.device drawmenubars -- org.eclipse.swt.widgets.display runpopups -- org.eclipse.swt.widgets.display filtermessage -- org.eclipse.swt.widgets.display windowproc -- org.eclipse.swt.widgets.display windowproc -- org.eclipse.swt.widgets.control WM_TIMER -- org.eclipse.swt.widgets.control windowproc -- org.eclipse.swt.widgets.display windowproc -- org.eclipse.swt.widgets.control WM_TIMER -- org.eclipse.swt.widgets.control windowproc -- org.eclipse.swt.widgets.display windowproc -- org.eclipse.swt.widgets.control
15 Scenario-Driven Approach Default: Given a textual change request, an Information Retrieval (IR) (e.g., Latent Semantic Indexing) is used to estimate the impact set. Scenario 3: Both verified starting entity and run-time information are available readanddispatch -- org.eclipse.swt.widgets.display checkdevice -- org.eclipse.swt.widgets.display isdisposed -- org.eclipse.swt.graphics.device drawmenubars -- org.eclipse.swt.widgets.display runpopups -- org.eclipse.swt.widgets.display filtermessage -- org.eclipse.swt.widgets.display windowproc -- org.eclipse.swt.widgets.display windowproc -- org.eclipse.swt.widgets.control WM_TIMER -- org.eclipse.swt.widgets.control windowproc -- org.eclipse.swt.widgets.display windowproc -- org.eclipse.swt.widgets.control WM_TIMER -- org.eclipse.swt.widgets.control windowproc -- org.eclipse.swt.widgets.display windowproc -- org.eclipse.swt.widgets.control
16 Approach (IR) IR (default): Analyzing textual information via IR
17 Approach (IR) IR (default): Analyzing textual information via IR Impact Set
18 Approach (IR+Dyn) IR+Dyn: Analyzing textual information via IR and execution information via dynamic analysis readanddispatch -- org.eclipse.swt.widgets.display checkdevice -- org.eclipse.swt.widgets.display isdisposed -- org.eclipse.swt.graphics.device drawmenubars -- org.eclipse.swt.widgets.display runpopups -- org.eclipse.swt.widgets.display filtermessage -- org.eclipse.swt.widgets.display windowproc -- org.eclipse.swt.widgets.display windowproc -- org.eclipse.swt.widgets.control WM_TIMER -- org.eclipse.swt.widgets.control windowproc -- org.eclipse.swt.widgets.display windowproc -- org.eclipse.swt.widgets.control WM_TIMER -- org.eclipse.swt.widgets.control windowproc -- org.eclipse.swt.widgets.display windowproc -- org.eclipse.swt.widgets.control
19 Approach (IR+Dyn) IR+Dyn: Analyzing textual information via IR and execution information via dynamic analysis readanddispatch -- org.eclipse.swt.widgets.display checkdevice -- org.eclipse.swt.widgets.display isdisposed -- org.eclipse.swt.graphics.device drawmenubars -- org.eclipse.swt.widgets.display runpopups -- org.eclipse.swt.widgets.display filtermessage -- org.eclipse.swt.widgets.display windowproc -- org.eclipse.swt.widgets.display windowproc -- org.eclipse.swt.widgets.control WM_TIMER -- org.eclipse.swt.widgets.control windowproc -- org.eclipse.swt.widgets.display windowproc -- org.eclipse.swt.widgets.control WM_TIMER -- org.eclipse.swt.widgets.control windowproc -- org.eclipse.swt.widgets.display windowproc -- org.eclipse.swt.widgets.control Impact Set
20 Approach (IR+Dyn+Hist) IR+Dyn+Hist: Analyzing textual information via IR, execution information via dynamic analysis, and history via data mining
21 Approach (IR+Hist) IR+Hist: Analyzing textual information via IR and history via data mining Impact Set
22 Approach (IR+Hist) IR+Hist: Analyzing textual information via IR and history via data mining readanddispatch -- org.eclipse.swt.widgets.display checkdevice -- org.eclipse.swt.widgets.display isdisposed -- org.eclipse.swt.graphics.device drawmenubars -- org.eclipse.swt.widgets.display runpopups -- org.eclipse.swt.widgets.display filtermessage -- org.eclipse.swt.widgets.display windowproc -- org.eclipse.swt.widgets.display windowproc -- org.eclipse.swt.widgets.control WM_TIMER -- org.eclipse.swt.widgets.control windowproc -- org.eclipse.swt.widgets.display windowproc -- org.eclipse.swt.widgets.control WM_TIMER -- org.eclipse.swt.widgets.control windowproc -- org.eclipse.swt.widgets.display windowproc -- org.eclipse.swt.widgets.control
23 Approach (IR+Hist) IR+Hist: Analyzing textual information via IR and history via data mining Impact Set readanddispatch -- org.eclipse.swt.widgets.display checkdevice -- org.eclipse.swt.widgets.display isdisposed -- org.eclipse.swt.graphics.device drawmenubars -- org.eclipse.swt.widgets.display runpopups -- org.eclipse.swt.widgets.display filtermessage -- org.eclipse.swt.widgets.display windowproc -- org.eclipse.swt.widgets.display windowproc -- org.eclipse.swt.widgets.control WM_TIMER -- org.eclipse.swt.widgets.control windowproc -- org.eclipse.swt.widgets.display windowproc -- org.eclipse.swt.widgets.control WM_TIMER -- org.eclipse.swt.widgets.control windowproc -- org.eclipse.swt.widgets.display windowproc -- org.eclipse.swt.widgets.control
24 Impact Analysis - Motivating Example ArgoUML Bug #2472: Wrong keyboard focus in settings dialog after close & reopen [ ] 16 methods impacted by bug #2472 IR (default):! 2,16,30, IR+Dyn! 1,3,5,7,11,12,14,29,
25 Impact Analysis - Case Study Four open source software systems, namely ArgoUML, JabRef, jedit and mucommander Commits in the version history used as ground truth, i.e., actual impact sets Widely used metrics precision (false positives), recall (false negatives), and f-measure (combination of precision and recall) used for accuracy measure System Version LOC Files Methods Terms ArgoUML K 503 6K 4K JabRef K 1,439 11K 5K jedit K 1,069 8K 4K mucommander K 577 4K 5K
26 Impact Analysis - Research Question Does providing more information improve the accuracy of IA when compared to the default approach?
27 Impact Analysis - Main Results Is it possible to improve the accuracy? 20% 15% 10% Precision 5% CP5 CP10 CP20 CP30 CP40 IR IR+Dyn IR+Hist IR+Hist+Dyn 0%
28 Impact Analysis - Main Results Is it possible to improve the accuracy? 50% 38% 25% Precision 13% CP5 CP10 CP20 CP30 CP40 IR IR+Dyn IR+Hist IR+Hist+Dyn 0%
29 Impact Analysis - Main Results The best results are obtained in scenarios where both a verified starting entities and execution information are available. Recall improvements of up to 41% over the default approach and up to 17% over the evolutionary technique in ibatis
30 Impact Analysis - Main Results The best results are obtained in scenarios where both a verified starting entities and execution information are available. Are our results statistically significant? Recall improvements of up to 41% over the default approach and up to 17% over the evolutionary technique in ibatis
31 Impact Analysis - Statistical Test Does providing more information significantly improve results of impact analysis compared to using the default approach?
32 Impact Analysis - Results of Wilcoxon Signed-Rank Test System H 0 P1 H 0 R1 H 0 P2 H 0 R2 H 0 P3 H 0 R3 ArgoUML < < < < < < JabRef < < jedit < < < < < mucommander < < < < < H 0 P1 : IR+Dyn does not significantly improve precision (compared to IR) H 0 R1 : IR+Dyn does not significantly improve recall (compared to IR) H 0 P2 : IR+Hist does not significantly improve precision (compared to IR) H 0 R2 : IR+Hist does not significantly improve recall (compared to IR) H 0 P3 : IR+Dyn+Hist does not significantly improve precision (compared to IR) H 0 R3 : IR+Dyn+Hist does not significantly improve recall (compared to IR)
33 Impact Analysis - Results of Wilcoxon Signed-Rank Test System H 0 P1 H 0 R1 H 0 P2 H 0 R2 H 0 P3 H 0 R3 ArgoUML < < < < < < JabRef < < jedit < < < < < Results are statistically significant! mucommander < < < < < H 0 P1 : IR+Dyn does not significantly improve precision (compared to IR) H 0 R1 : IR+Dyn does not significantly improve recall (compared to IR) H 0 P2 : IR+Hist does not significantly improve precision (compared to IR) H 0 R2 : IR+Hist does not significantly improve recall (compared to IR) H 0 P3 : IR+Dyn+Hist does not significantly improve precision (compared to IR) H 0 R3 : IR+Dyn+Hist does not significantly improve recall (compared to IR)
34 Threats to Validity Commits used as gold standard for accuracy computation Not all the entities in a commit maybe related to a single change request All the entities related to a single change request maybe present in a single commit Developer established actual change-sets Quality of dynamic traces obtained for change request Statistically significant results for the four open source Java systems may not generalize
35 Conclusion Scenario-driven combination of IR, dynamic analysis and MSR techniques for IA Recall improvements of up to 41% over the default approach Precision improvement up to 17% over the default approach
36 Thank You William and Mary
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