Efficient regression testing of distributed real-time reactive systems in the context of model-driven development
Regression testing is indispensable, especially for real-time distributed systems to ensure that existing functionalities are not affected by changes. Despite recent advances, regression testing for distributed systems remains challenging and extremely costly. Existing techniques often require runni...
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| Vydáno v: | Software and systems modeling Ročník 22; číslo 5; s. 1565 - 1587 |
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| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Berlin/Heidelberg
Springer Berlin Heidelberg
01.10.2023
Springer Nature B.V |
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| ISSN: | 1619-1366, 1619-1374 |
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| Abstract | Regression testing is indispensable, especially for real-time distributed systems to ensure that existing functionalities are not affected by changes. Despite recent advances, regression testing for distributed systems remains challenging and extremely costly. Existing techniques often require running a failing system several times before detecting a regression. As a result, conventional approaches that use re-execution without considering the inherent non-determinism of distributed systems, and providing no (or low) control over execution are inadequate in many ways. In this paper, we present
MRegTest
, a replay-based regression testing framework in the context of model-driven development to facilitate deterministic replay of traces for detecting regressions while offering sufficient control for the purpose of testing over the execution of the changed system. The experimental results show that compared to the traditional approaches that annotate traces with timestamps and variable values
MRegTest
detects almost all regressions while reducing the size of the trace significantly and incurring similar runtime overhead. |
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| AbstractList | Regression testing is indispensable, especially for real-time distributed systems to ensure that existing functionalities are not affected by changes. Despite recent advances, regression testing for distributed systems remains challenging and extremely costly. Existing techniques often require running a failing system several times before detecting a regression. As a result, conventional approaches that use re-execution without considering the inherent non-determinism of distributed systems, and providing no (or low) control over execution are inadequate in many ways. In this paper, we present MRegTest, a replay-based regression testing framework in the context of model-driven development to facilitate deterministic replay of traces for detecting regressions while offering sufficient control for the purpose of testing over the execution of the changed system. The experimental results show that compared to the traditional approaches that annotate traces with timestamps and variable values MRegTest detects almost all regressions while reducing the size of the trace significantly and incurring similar runtime overhead. Regression testing is indispensable, especially for real-time distributed systems to ensure that existing functionalities are not affected by changes. Despite recent advances, regression testing for distributed systems remains challenging and extremely costly. Existing techniques often require running a failing system several times before detecting a regression. As a result, conventional approaches that use re-execution without considering the inherent non-determinism of distributed systems, and providing no (or low) control over execution are inadequate in many ways. In this paper, we present MRegTest , a replay-based regression testing framework in the context of model-driven development to facilitate deterministic replay of traces for detecting regressions while offering sufficient control for the purpose of testing over the execution of the changed system. The experimental results show that compared to the traditional approaches that annotate traces with timestamps and variable values MRegTest detects almost all regressions while reducing the size of the trace significantly and incurring similar runtime overhead. |
| Author | Babaei, Majid Dingel, Juergen |
| Author_xml | – sequence: 1 givenname: Majid surname: Babaei fullname: Babaei, Majid email: babaei@cs.queensu.ca organization: School of Computing Queen’s University – sequence: 2 givenname: Juergen surname: Dingel fullname: Dingel, Juergen organization: Computing Queen’s University |
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| CitedBy_id | crossref_primary_10_1016_j_infsof_2024_107492 crossref_primary_10_1016_j_jss_2025_112508 |
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| Copyright_xml | – notice: The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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