DocumentCode :
725866
Title :
Mining Patterns of Unsatisfiable Constraints to Detect Infeasible Paths
Author :
Sun Ding ; Hee Beng Kuan Tan ; Lwin Khin Shar
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore
fYear :
2015
fDate :
23-24 May 2015
Firstpage :
65
Lastpage :
69
Abstract :
Detection of infeasible paths is required in many areas including test coverage analysis, test case generation, security vulnerability analysis, etc. Existing approaches typically use static analysis coupled with symbolic evaluation, heuristics, or path-pattern analysis. This paper is related to these approaches but with a different objective. It is to analyze code of real systems to build patterns of unsatisfiable constraints in infeasible paths. The resulting patterns can be used to detect infeasible paths without the use of constraint solver and evaluation of function calls involved, thus improving scalability. The patterns can be built gradually. Evaluation of the proposed approach shows promising results.
Keywords :
data mining; infeasible paths detection; pattern mining; unsatisfiable constraints; Accuracy; Pattern matching; Prototypes; Scalability; Software; Testing; Training; Infeasible paths; pattern mining; static analysis; structural testing; symbolic evaluation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automation of Software Test (AST), 2015 IEEE/ACM 10th International Workshop on
Conference_Location :
Florence
Type :
conf
DOI :
10.1109/AST.2015.21
Filename :
7166270
Link To Document :
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