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Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-18598
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dc.contributor.authorGrano, Giovanni-
dc.contributor.authorLaaber, Christoph-
dc.contributor.authorPanichella, Annibale-
dc.contributor.authorPanichella, Sebastiano-
dc.date.accessioned2019-10-31T14:04:23Z-
dc.date.available2019-10-31T14:04:23Z-
dc.date.issued2019-
dc.identifier.issn0098-5589de_CH
dc.identifier.issn1939-3520de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/18598-
dc.description​© 2019 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.de_CH
dc.description.abstractAutomated test case generation is an effective technique to yield high-coverage test suites. While the majority of research effort has been devoted to satisfying coverage criteria, a recent trend emerged towards optimizing other non-coverage aspects. In this regard, runtime and memory usage are two essential dimensions: less expensive tests reduce the resource demands for the generation process and later regression testing phases. This study shows that performance-aware test case generation requires solving two main challenges: providing a good approximation of resource usage with minimal overhead and avoiding detrimental effects on both final coverage and fault detection effectiveness. To tackle these challenges, we conceived a set of performance proxies-inspired by previous work on performance testing- that provide a reasonable estimation of the test execution costs (i.e., runtime and memory usage). Thus, we propose an adaptive strategy, called aDynaMOSA, which leverages these proxies by extending DynaMOSA, a state-of-the-art evolutionary algorithm in unit testing. Our empirical study-involving 110 non-trivial Java classes- reveals that our adaptive approach generates test suite with statistically significant improvements in runtime (-25%) and heap memory consumption (-15%) compared to DynaMOSA. Additionally, aDynaMOSA has comparable results to DynaMOSA over seven different coverage criteria and similar fault detection effectiveness. Our empirical investigation also highlights that the usage of performance proxies (i.e., without the adaptiveness) is not sufficient to generate more performant test cases without compromising the overall coverage.de_CH
dc.language.isoende_CH
dc.publisherIEEEde_CH
dc.relation.ispartofIEEE Transactions on Software Engineeringde_CH
dc.rightsLicence according to publishing contractde_CH
dc.subject.ddc005: Computerprogrammierung, Programme und Datende_CH
dc.titleTesting with fewer resources : an adaptive approach to performance-aware test case generationde_CH
dc.typeBeitrag in wissenschaftlicher Zeitschriftde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Informatik (InIT)de_CH
dc.identifier.doi10.1109/TSE.2019.2946773de_CH
dc.identifier.doi10.21256/zhaw-18598-
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.publication.statusacceptedVersionde_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.webfeedService Engineeringde_CH
zhaw.author.additionalNode_CH
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Grano, G., Laaber, C., Panichella, A., & Panichella, S. (2019). Testing with fewer resources : an adaptive approach to performance-aware test case generation. IEEE Transactions on Software Engineering. https://doi.org/10.1109/TSE.2019.2946773
Grano, G. et al. (2019) ‘Testing with fewer resources : an adaptive approach to performance-aware test case generation’, IEEE Transactions on Software Engineering [Preprint]. Available at: https://doi.org/10.1109/TSE.2019.2946773.
G. Grano, C. Laaber, A. Panichella, and S. Panichella, “Testing with fewer resources : an adaptive approach to performance-aware test case generation,” IEEE Transactions on Software Engineering, 2019, doi: 10.1109/TSE.2019.2946773.
GRANO, Giovanni, Christoph LAABER, Annibale PANICHELLA und Sebastiano PANICHELLA, 2019. Testing with fewer resources : an adaptive approach to performance-aware test case generation. IEEE Transactions on Software Engineering. 2019. DOI 10.1109/TSE.2019.2946773
Grano, Giovanni, Christoph Laaber, Annibale Panichella, and Sebastiano Panichella. 2019. “Testing with Fewer Resources : An Adaptive Approach to Performance-Aware Test Case Generation.” IEEE Transactions on Software Engineering. https://doi.org/10.1109/TSE.2019.2946773.
Grano, Giovanni, et al. “Testing with Fewer Resources : An Adaptive Approach to Performance-Aware Test Case Generation.” IEEE Transactions on Software Engineering, 2019, https://doi.org/10.1109/TSE.2019.2946773.


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