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Title: Discovering complete API rules with mutation testing
Authors: Nguyen, A.C.
Khoo, S.-C. 
Keywords: formal specifications
mutation testing
specification mining
Issue Date: 2012
Citation: Nguyen, A.C.,Khoo, S.-C. (2012). Discovering complete API rules with mutation testing. IEEE International Working Conference on Mining Software Repositories : 151-160. ScholarBank@NUS Repository.
Abstract: Specifications are important for many activities during software construction and maintenance process such as testing, verification, debugging and repairing. Despite their importance, specifications are often missing, informal or incomplete because they are difficult to write manually. Many techniques have been proposed to automatically mine specifications describing method call sequence from execution traces or source code using frequent pattern mining. Unfortunately, a sizeable number of such "interesting" specifications discovered by frequent pattern mining may not capture the correct use patterns of method calls. Consequently, when used in software testing or verification, these mined specifications lead to many false positive defects, which in turn consume much effort for manual investigation. We present a novel framework for automatically discovering legitimate specifications from execution traces using a mutation testing based approach. Such an approach gives a semantics bearing to the legitimacy of the discovered specifications. We introduce the notion of maximal precision and completeness as the desired forms of discovered specifications, and describe in detail suppression techniques that aid efficient discovery. Preliminary evaluation of this approach on several open source software projects shows that specifications discovered through our approach, compared with those discovered through frequent pattern mining, are much more precise and complete. When used in finding bugs, our specifications also locate defects with significantly fewer false positives and more true positives. © 2012 IEEE.
Source Title: IEEE International Working Conference on Mining Software Repositories
ISBN: 9781467317610
ISSN: 21601852
DOI: 10.1109/MSR.2012.6224275
Appears in Collections:Staff Publications

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