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dc.contributor.authorTsankov, Petar
dc.contributor.authorJin, Wei
dc.contributor.authorOrso, Alessandro
dc.contributor.authorSinha, Saurabh
dc.date.accessioned2011-02-16T17:30:00Z
dc.date.available2011-02-16T17:30:00Z
dc.date.issued2010
dc.identifier.urihttp://hdl.handle.net/1853/36919
dc.description.abstractTypically, dynamic-analysis techniques operate on a small subset of all possible program behaviors, which limits their effectiveness and the representativeness of the computed results. To address this issue, a new paradigm is emerging: execution hijacking—techniques that explore a larger set of program behaviors by forcing executions along specific paths. Although hijacked executions are infeasible for the given inputs, they can still produce feasible behaviors that could be observed under other inputs. In such cases, execution hijacking can improve the effectiveness of dynamic analysis without requiring the (expensive) generation of additional inputs. To evaluate the usefulness of execution hijacking, we defined, implemented, and evaluated several variants of it. Specifically, we performed empirical study where we assessed whether execution hijacking could improve the effectiveness of two common dynamic analyses: software testing and memory error detection. The results of the study show that execution hijacking, if suitably performed, can indeed help dynamic analysis techniques.en_US
dc.language.isoen_USen_US
dc.publisherGeorgia Institute of Technologyen_US
dc.relation.ispartofseriesCERCS ; GIT-CERCS-10-12en_US
dc.subjectDynamic analysisen_US
dc.subjectExecution hijackingen_US
dc.subjectMemory error detectionen_US
dc.subjectSoftware testingen_US
dc.titleExecution Hijacking: Improving Dynamic Analysis by Flying off Courseen_US
dc.typeTechnical Reporten_US
dc.contributor.corporatenameGeorgia Institute of Technology. College of Computing
dc.contributor.corporatenameGeorgia Institute of Technology. Center for Experimental Research in Computer Systems
dc.contributor.corporatenameIBM Research


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