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- Title
Discovering Neglected Conditions in Software by Mining Dependence Graphs.
- Authors
Ray-Yaung Chang; Podgurski, Andy; Jiong Yang
- Abstract
Neglected conditions are an important but difficult-to-find class of software defects. This paper presents a novel approach for revealing neglected conditions that integrates static program analysis and advanced data mining techniques to discover implicit conditional rules in a code base and to discover rule violations that indicate neglected conditions. The approach requires the user to indicate minimal constraints on the context of the rules to be sought, rather than specific rule templates. To permit this generality, rules are modeled as graph minors of enhanced procedure dependence graphs (EPDGs), in which control and data dependence edges are augmented by edges representing shared data dependences. A heuristic maximal frequent subgraph mining algorithm is used to extract candidate rules from EPDGs and a heuristic graph matching algorithm is used to identify rule violations. We also report the results of an empirical study in which the approach was applied to four open source projects (openssl, make, procmail, amaya). These results indicate that the approach is effective and reasonably efficient.
- Subjects
SOFTWARE engineering; AUTOMATION; DATA mining; SOFTWARE failures; COMPUTER software quality control; COMPUTER software usability
- Publication
IEEE Transactions on Software Engineering, 2008, Vol 34, Issue 5, p579
- ISSN
0098-5589
- Publication type
Article
- DOI
10.1109/TSE.2008.24