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dc.contributor.authorGao, Ruizhien_US
dc.contributor.authorHu, Linghuanen_US
dc.contributor.authorWong, W. Ericen_US
dc.contributor.authorLu, Han-Linen_US
dc.contributor.authorHuang, Shih-Kunen_US
dc.date.accessioned2017-04-21T06:49:26Z-
dc.date.available2017-04-21T06:49:26Z-
dc.date.issued2016en_US
dc.identifier.isbn978-1-5090-3713-1en_US
dc.identifier.urihttp://dx.doi.org/10.1109/QRS-C.2016.11en_US
dc.identifier.urihttp://hdl.handle.net/11536/136258-
dc.description.abstractComplex software systems present significant challenges to existing software testing techniques. Simply applying exhaustive testing will lead to the execution of a prohibitively large number of test cases. Furthermore, many testing techniques today provide neither promising coverage achievement nor reliable fault detection strength. In this paper, we propose a technique, which represents an innovative synthesis of combinatorial testing and symbolic execution, to generate test cases based on a novel coverage criterion, namely combinatorial decision coverage (CDC). Strength t (or t-way) CDC requires each t-tuple of decision outcomes to be executed by at least one test case. Given a program, our CDC-based technique first uses a revised version of a symbolic executor, (SE)-E-2, to collect all program decisions with symbolic variables as well as their corresponding constraints and then applies a combinatorial test generation tool, ACTS, to generate t-way combinations for the outcomes of these decisions. A test case can be generated with respect to each combination that represents a single path-condition of the program. Case studies were conducted on three versions of photo editing applications. Our results indicate that a test set generated using the proposed technique has higher statement, decision, and all-use coverage as well as better fault detection strength than a test set of the same size generated by random testing and genetic algorithm-based test generation.en_US
dc.language.isoen_USen_US
dc.subjectcombinatorial decision coverageen_US
dc.subjectsymbolic executionen_US
dc.subjecttest case generationen_US
dc.subjectfault detectionen_US
dc.titleEffective Test Generation for Combinatorial Decision Coverageen_US
dc.typeProceedings Paperen_US
dc.identifier.doi10.1109/QRS-C.2016.11en_US
dc.identifier.journal2016 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE QUALITY, RELIABILITY AND SECURITY COMPANION (QRS-C 2016)en_US
dc.citation.spage47en_US
dc.citation.epage54en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000386627300007en_US
dc.citation.woscount0en_US
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