DocumentCode
2441674
Title
Extending static analysis by mining project-specific rules
Author
Sun, Boya ; Shu, Gang ; Podgurski, Andy ; Robinson, Brian
Author_Institution
EECS Dept., Case Western Reserve Univ., Cleveland, OH, USA
fYear
2012
fDate
2-9 June 2012
Firstpage
1054
Lastpage
1063
Abstract
Commercial static program analysis tools can be used to detect many defects that are common across applications. However, such tools currently have limited ability to reveal defects that are specific to individual projects, unless specialized checkers are devised and implemented by tool users. Developers do not typically exploit this capability. By contrast, defect mining tools developed by researchers can discover project-specific defects, but they require specialized expertise to employ and they may not be robust enough for general use. We present a hybrid approach in which a sophisticated dependence-based rule mining tool is used to discover project-specific programming rules, which are then transformed automatically into checkers that a commercial static analysis tool can run against a code base to reveal defects. We also present the results of an empirical study in which this approach was applied successfully to two large industrial code bases. Finally, we analyze the potential implications of this approach for software development practice.
Keywords
data mining; program diagnostics; project management; software engineering; software management; software tools; commercial analysis tools; defect mining tools; defects detection; dependence-based rule mining tool; individual projects; industrial code bases; project-specific defects; project-specific programming rules; project-specific rules mining; software development practice; specialized checkers; Data mining; Engines; Generators; Programming; Software; Transforms; XML; defect mining; program dependence graphs; static program analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Engineering (ICSE), 2012 34th International Conference on
Conference_Location
Zurich
ISSN
0270-5257
Print_ISBN
978-1-4673-1066-6
Electronic_ISBN
0270-5257
Type
conf
DOI
10.1109/ICSE.2012.6227114
Filename
6227114
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