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Article: Improving the effectiveness of testing pervasive software via context diversity

TitleImproving the effectiveness of testing pervasive software via context diversity
Authors
Issue Date2014
PublisherAssociation for Computing Machinery, Inc. The Journal's web site is located at http://taas.acm.org
Citation
ACM Transactions on Autonomous and Adaptive Systems, 2014, v. 9 n. 2, article no. 9, p. 9:1-9:28 How to Cite?
AbstractContext-aware pervasive software is responsive to various contexts and their changes. A faulty implementation of the context-aware features may lead to unpredictable behavior with adverse effects. In software testing, one of the most important research issues is to determine the sufficiency of a test suite to verify the software under test. Existing adequacy criteria for testing traditional software, however, have not explored the dimension of serial test inputs and have not considered context changes when constructing test suites. In this article, we define the concept of context diversity to capture the extent of context changes in serial inputs and propose three strategies to study how context diversity may improve the effectiveness of the data-flow testing criteria. Our case study shows that the strategy that uses test cases with higher context diversity can significantly improve the effectiveness of existing data-flow testing criteria for context-aware pervasive software. In addition, test suites with higher context diversity are found to execute significantly longer paths, which may provide a clue that reveals why context diversity can contribute to the improvement of effectiveness of test suites. © 2014 ACM.
Persistent Identifierhttp://hdl.handle.net/10722/199520
ISSN
2015 Impact Factor: 1.118
2015 SCImago Journal Rankings: 0.797

 

DC FieldValueLanguage
dc.contributor.authorWang, H-
dc.contributor.authorChan, WK-
dc.contributor.authorTse, TH-
dc.date.accessioned2014-07-22T01:21:49Z-
dc.date.available2014-07-22T01:21:49Z-
dc.date.issued2014-
dc.identifier.citationACM Transactions on Autonomous and Adaptive Systems, 2014, v. 9 n. 2, article no. 9, p. 9:1-9:28-
dc.identifier.issn1556-4665-
dc.identifier.urihttp://hdl.handle.net/10722/199520-
dc.description.abstractContext-aware pervasive software is responsive to various contexts and their changes. A faulty implementation of the context-aware features may lead to unpredictable behavior with adverse effects. In software testing, one of the most important research issues is to determine the sufficiency of a test suite to verify the software under test. Existing adequacy criteria for testing traditional software, however, have not explored the dimension of serial test inputs and have not considered context changes when constructing test suites. In this article, we define the concept of context diversity to capture the extent of context changes in serial inputs and propose three strategies to study how context diversity may improve the effectiveness of the data-flow testing criteria. Our case study shows that the strategy that uses test cases with higher context diversity can significantly improve the effectiveness of existing data-flow testing criteria for context-aware pervasive software. In addition, test suites with higher context diversity are found to execute significantly longer paths, which may provide a clue that reveals why context diversity can contribute to the improvement of effectiveness of test suites. © 2014 ACM.-
dc.languageeng-
dc.publisherAssociation for Computing Machinery, Inc. The Journal's web site is located at http://taas.acm.org-
dc.relation.ispartofACM Transactions on Autonomous and Adaptive Systems-
dc.rightsACM Transactions on Autonomous and Adaptive Systems. Copyright © Association for Computing Machinery, Inc.-
dc.rights©ACM, 2014. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Transactions on Autonomous and Adaptive Systems, 2014, v. 9 n. 2, article no. 9, p. 9:1-9:28. http://doi.acm.org/10.1145/2620000-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleImproving the effectiveness of testing pervasive software via context diversity-
dc.typeArticle-
dc.identifier.emailChan, WK: rickchan@hkucc.hku.hk-
dc.identifier.emailTse, TH: thtse@cs.hku.hk-
dc.identifier.authorityTse, TH=rp00546-
dc.description.naturepostprint-
dc.identifier.doi10.1145/2620000-
dc.identifier.scopuseid_2-s2.0-84906849956-
dc.identifier.hkuros230248-
dc.identifier.volume9-
dc.identifier.issue2-
dc.identifier.spage9:1-
dc.identifier.epage9:28-
dc.publisher.placeUnited States-

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