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Mining Patterns of Unsatisfiable Constraints to Detect Infeasible Paths
DING, SUN; TAN, HEE BENG KUAN; Shar, Lwin Khin
2015In Automation of Software Test (AST 2015)
Peer reviewed
 

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Keywords :
infeasible paths; pattern mining; symbolic evaluation
Abstract :
[en] 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.
Disciplines :
Computer science
Author, co-author :
DING, SUN;  Nanyang Technological University > Information Engineering, School of Electrical and Electronic Engineering
TAN, HEE BENG KUAN
Shar, Lwin Khin ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
External co-authors :
yes
Language :
English
Title :
Mining Patterns of Unsatisfiable Constraints to Detect Infeasible Paths
Publication date :
May 2015
Event name :
10th International Workshop on Automation of Software Test in conjunction with 37th International Conference on Software Engineering
Event date :
23-05-2015 to 24-05-2015
Audience :
International
Journal title :
Automation of Software Test (AST 2015)
Peer reviewed :
Peer reviewed
Available on ORBilu :
since 10 December 2015

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