Hierons, R. orcid.org/0000-0002-4771-1446, Li, M., Liu, X. et al. (3 more authors) (2020) Many-objective test suite generation for software product lines. ACM Transactions on Software Engineering and Methodology, 29 (1). 2. ISSN 1049-331X
Abstract
A Software Product Line (SPL) is a set of products built from a number of features, the set of valid products being defined by a feature model. Typically, it does not make sense to test all products defined by an SPL and one instead chooses a set of products to test (test selection) and, ideally, derives a good order in which to test them (test prioritisation). Since one cannot know in advance which products will reveal faults, test selection and prioritisation are normally based on objective functions that are known to relate to likely effectiveness or cost. This paper introduces a new technique, the grid-based evolution strategy (GrES), which considers several objective functions that assess a selection or prioritisation and aims to optimise on all of these. The problem is thus a many-objective optimisation problem. We use a new approach, in which all of the objective functions are considered but one (pairwise coverage) is seen as the most important. We also derive a novel evolution strategy based on domain knowledge. The results of the evaluation, on randomly generated and realistic feature models, were promising, with GrES outperforming previously proposed techniques and a range of many-objective optimisation algorithms.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 Association for Computing Machinery. This is an author-produced version of a paper subsequently published in ACM Transactions on Software Engineering and Methodology. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Software Product Line; Test Selection; Test Prioritisation; Multi-objective optimisation |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 17 Sep 2019 11:46 |
Last Modified: | 22 Jun 2020 15:45 |
Status: | Published |
Publisher: | Association for Computing Machinery |
Refereed: | Yes |
Identification Number: | 10.1145/3361146 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:150616 |