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Article: Exploiting the largest available zone: A proactive approach to adaptive random testing by exclusion

TitleExploiting the largest available zone: A proactive approach to adaptive random testing by exclusion
Authors
KeywordsSubspace constraints
Software
Strips
Time complexity
Software testing
Issue Date2020
PublisherInstitute of Electrical and Electronics Engineers (IEEE): OAJ. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6287639
Citation
IEEE Access, 2020, v. 8, p. 52475-52488 How to Cite?
AbstractAdaptive random testing (ART) has been proposed to enhance the effectiveness of random testing (RT) through more even spreading of the test cases. In particular, restricted random testing (RRT) is an ART algorithm based on the intuition of skipping all the candidate test cases that are within the neighborhoods (or zones) of previously executed test cases. RRT has higher effectiveness than RT in terms of failure detection but incurs a higher time cost. In this paper, we aim to further reduce the time costs for RRT and improve the effectiveness for RT and ART methods. We propose a proactive technique known as “RRT by largest available zone” (RRT-LAZ). Like RRT, RRT-LAZ first defines an exclusion zone around every executed test case in order to determine the available zones. Unlike the original RRT, RRT-LAZ then compares all the available zones to proactively pick the largest one, from which the next test case is randomly generated. Both simulation analyses and empirical studies have been employed to investigate the efficiency and effectiveness of RRT-LAZ in relation to RT and related ART algorithms. The results show that RRT-LAZ has significantly lower time costs than RRT. Furthermore, RRT-LAZ is more effective than RT and related ART methods for block failure patterns in low-dimensional input spaces. In general, since RRT-LAZ employs a proactive technique instead of a passive one in generating next cases, it is much more cost-effective than RRT. RRT-LAZ is also more cost-effective than RT and other ART methods that we have studied.
Descriptioneid_2-s2.0-85082526533
Persistent Identifierhttp://hdl.handle.net/10722/286499
ISSN
2019 Impact Factor: 3.745
2015 SCImago Journal Rankings: 0.947

 

DC FieldValueLanguage
dc.contributor.authorChen, J-
dc.contributor.authorBao, Q-
dc.contributor.authorTse, TH-
dc.contributor.authorChen, TY-
dc.contributor.authorXi, J-
dc.contributor.authorMao, C-
dc.contributor.authorYu, M-
dc.contributor.authorHuang, R-
dc.date.accessioned2020-08-31T07:04:43Z-
dc.date.available2020-08-31T07:04:43Z-
dc.date.issued2020-
dc.identifier.citationIEEE Access, 2020, v. 8, p. 52475-52488-
dc.identifier.issn2169-3536-
dc.identifier.urihttp://hdl.handle.net/10722/286499-
dc.descriptioneid_2-s2.0-85082526533-
dc.description.abstractAdaptive random testing (ART) has been proposed to enhance the effectiveness of random testing (RT) through more even spreading of the test cases. In particular, restricted random testing (RRT) is an ART algorithm based on the intuition of skipping all the candidate test cases that are within the neighborhoods (or zones) of previously executed test cases. RRT has higher effectiveness than RT in terms of failure detection but incurs a higher time cost. In this paper, we aim to further reduce the time costs for RRT and improve the effectiveness for RT and ART methods. We propose a proactive technique known as “RRT by largest available zone” (RRT-LAZ). Like RRT, RRT-LAZ first defines an exclusion zone around every executed test case in order to determine the available zones. Unlike the original RRT, RRT-LAZ then compares all the available zones to proactively pick the largest one, from which the next test case is randomly generated. Both simulation analyses and empirical studies have been employed to investigate the efficiency and effectiveness of RRT-LAZ in relation to RT and related ART algorithms. The results show that RRT-LAZ has significantly lower time costs than RRT. Furthermore, RRT-LAZ is more effective than RT and related ART methods for block failure patterns in low-dimensional input spaces. In general, since RRT-LAZ employs a proactive technique instead of a passive one in generating next cases, it is much more cost-effective than RRT. RRT-LAZ is also more cost-effective than RT and other ART methods that we have studied.-
dc.languageeng-
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE): OAJ. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6287639-
dc.relation.ispartofIEEE Access-
dc.rightsIEEE Access. Copyright © Institute of Electrical and Electronics Engineers (IEEE): OAJ.-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectSubspace constraints-
dc.subjectSoftware-
dc.subjectStrips-
dc.subjectTime complexity-
dc.subjectSoftware testing-
dc.titleExploiting the largest available zone: A proactive approach to adaptive random testing by exclusion-
dc.typeArticle-
dc.identifier.emailTse, TH: thtse@cs.hku.hk-
dc.identifier.authorityTse, TH=rp00546-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/ACCESS.2020.2977777-
dc.identifier.hkuros313730-
dc.identifier.volume8-
dc.identifier.spage52475-
dc.identifier.epage52488-
dc.publisher.placeUnited States-

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