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Article: Beating random test case prioritization

TitleBeating random test case prioritization
Authors
KeywordsAdaptive random sequence
Adaptive random testing (ART)
Dispersity
Dispersity metric
Dispersity-based prioritization
Dissimilarity
Natural distance
Random prioritization (RP)
Issue Date2021
PublisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp/?punumber=24
Citation
IEEE Transactions on Reliability, 2021, v. 70 n. 2, p. 654-675 How to Cite?
AbstractExisting test case prioritization (TCP) techniques have limitations when applied to real-world projects, because these techniques require certain information to be made available before they can be applied. For example, the family of input-based TCP techniques are based on test case values or test script strings; other techniques use test coverage, test history, program structure, or requirements information. Existing techniques also cannot guarantee to always be more effective than random prioritization (RP) that does not have any precondition. As a result, RP remains the most applicable and most fundamental TCP technique. This article proposes an extremely simple, effective, and efficient way to prioritize test cases through the introduction of a dispersity metric. Our technique is as applicable as RP. We conduct empirical studies using 43 different versions of 15 real-world projects. Empirical results show that our technique is more effective than RP. Our algorithm has a linear computational complexity and, therefore, provides a practical solution to the problem of prioritizing very large test suites (such as those containing hundreds of thousands, or millions, of test cases), where the execution time of conventional nonlinear prioritization algorithms can be prohibitive. Our technique also provides a practical solution to TCP when neither input-based nor execution-based techniques are applicable due to lack of information.
Persistent Identifierhttp://hdl.handle.net/10722/286498
ISSN
2023 Impact Factor: 5.0
2023 SCImago Journal Rankings: 1.511
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorZhou, ZQ-
dc.contributor.authorLiu, C-
dc.contributor.authorChen, TY-
dc.contributor.authorTse, TH-
dc.contributor.authorSusilo, W-
dc.date.accessioned2020-08-31T07:04:42Z-
dc.date.available2020-08-31T07:04:42Z-
dc.date.issued2021-
dc.identifier.citationIEEE Transactions on Reliability, 2021, v. 70 n. 2, p. 654-675-
dc.identifier.issn0018-9529-
dc.identifier.urihttp://hdl.handle.net/10722/286498-
dc.description.abstractExisting test case prioritization (TCP) techniques have limitations when applied to real-world projects, because these techniques require certain information to be made available before they can be applied. For example, the family of input-based TCP techniques are based on test case values or test script strings; other techniques use test coverage, test history, program structure, or requirements information. Existing techniques also cannot guarantee to always be more effective than random prioritization (RP) that does not have any precondition. As a result, RP remains the most applicable and most fundamental TCP technique. This article proposes an extremely simple, effective, and efficient way to prioritize test cases through the introduction of a dispersity metric. Our technique is as applicable as RP. We conduct empirical studies using 43 different versions of 15 real-world projects. Empirical results show that our technique is more effective than RP. Our algorithm has a linear computational complexity and, therefore, provides a practical solution to the problem of prioritizing very large test suites (such as those containing hundreds of thousands, or millions, of test cases), where the execution time of conventional nonlinear prioritization algorithms can be prohibitive. Our technique also provides a practical solution to TCP when neither input-based nor execution-based techniques are applicable due to lack of information.-
dc.languageeng-
dc.publisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp/?punumber=24-
dc.relation.ispartofIEEE Transactions on Reliability-
dc.rights©2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.subjectAdaptive random sequence-
dc.subjectAdaptive random testing (ART)-
dc.subjectDispersity-
dc.subjectDispersity metric-
dc.subjectDispersity-based prioritization-
dc.subjectDissimilarity-
dc.subjectNatural distance-
dc.subjectRandom prioritization (RP)-
dc.titleBeating random test case prioritization-
dc.typeArticle-
dc.identifier.emailTse, TH: thtse@cs.hku.hk-
dc.identifier.authorityTse, TH=rp00546-
dc.description.naturepostprint-
dc.identifier.doi10.1109/TR.2020.2979815-
dc.identifier.scopuseid_2-s2.0-85110627843-
dc.identifier.hkuros313729-
dc.identifier.volume70-
dc.identifier.issue2-
dc.identifier.spage654-
dc.identifier.epage675-
dc.identifier.isiWOS:000659549200019-
dc.publisher.placeUnited States-
dc.identifier.issnl0018-9529-

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