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Input Generation via Taintdata Identification: Finding Hidden Path in the Environment‐Intensive Program
Author(s) -
Lei Xue,
Huang Wei,
Fan Wenqing,
Yang Yixian
Publication year - 2015
Publication title -
chinese journal of electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.267
H-Index - 25
eISSN - 2075-5597
pISSN - 1022-4653
DOI - 10.1049/cje.2015.07.007
Subject(s) - identification (biology) , path (computing) , computer science , computer network , biology , botany
Concolic testing is an integrated approachof symbolic execution and dynamic analysis, which iswidely adopted by security researchers for program behavioranalysis. This approach fails on hidden path discoveryof environment‐intensive program. We investigated onexisting concolic testing tools and found out that severalof them does not take this issue into account while otherssolved this issue with overloaded working model. Weproposed a systematic and unified approach of automaticallyidentifying and modifying the output of the Datainput interacting functions (DIIF) based on fine‐grainedtaint analysis, which detects and updates the data interactingwith the runtime environment and generating a newcustomized set of inputs to execute hidden paths, to revealthe hidden paths on only particular runtime configurationor context. A prototype was developed and evaluated witha set of complex and environment‐intensive programs. Theexperimental result demonstrated that our approach coulddetect the DIIF precisely and improve the code coverage.

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