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Improving continuous integration with similarity-based test case selection

Paper i proceeding
Författare Francisco Gomes de Oliveira Neto
Azeem Ahmad
Ola Leifler
Kristian Sandahl
Eduard Enoiu
Publicerad i Proceedings of the 13th International Workshop on Automation of Software Test
ISBN 978-1-4503-5743-2
ISSN 0270-5257
Förlag ACM
Publiceringsår 2018
Publicerad vid Institutionen för data- och informationsteknik, Software Engineering (GU)
Språk en
Länkar https://dl.acm.org/citation.cfm?id=...
https://dx.doi.org/10.1145/3194733....
Ämnesord automated testing, continuous integration, similarity based test case selection
Ämneskategorier Programvaruteknik

Sammanfattning

Automated testing is an essential component of Continuous Integration (CI) and Delivery (CD), such as scheduling automated test sessions on overnight builds. That allows stakeholders to execute entire test suites and achieve exhaustive test coverage, since running all tests is often infeasible during work hours, i.e., in parallel to development activities. On the other hand, developers also need test feedback from CI servers when pushing changes, even if not all test cases are executed. In this paper we evaluate similarity-based test case selection (SBTCS) on integration-level tests executed on continuous integration pipelines of two companies. We select test cases that maximise diversity of test coverage and reduce feedback time to developers. Our results confirm existing evidence that SBTCS is a strong candidate for test optimisation, by reducing feedback time (up to 92% faster in our case studies) while achieving full test coverage using only information from test artefacts themselves.

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