Akgun, Ozgur, Gent, Ian Philip, Jefferson, Christopher Anthony et al. (2 more authors) (2018) Metamorphic testing of constraint solvers. In: Hooker, John, (ed.) Principles and Practice of Constraint Programming - 24th International Conference, CP 2018, Proceedings:24th International Conference, CP 2018, Lille, France, August 27-31, 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) . Springer , Netherlands , pp. 727-736.
Abstract
Constraint solvers are complex pieces of software and are notoriously difficult to debug. In large part this is due to the difficulty of pinpointing the source of an error in the vast searches these solvers perform, since the effect of an error may only come to light long after the error is made. In addition, an error does not necessarily lead to the wrong result, further complicating the debugging process. A major source of errors in a constraint solver is the complex constraint propagation algorithms that provide the inference that controls and directs the search. In this paper we show that metamorphic testing is a principled way to test constraint solvers by comparing two different implementations of the same constraint. Specifically, specialised propagators for the constraint are tested against the general purpose table constraint propagator. We report on metamorphic testing of the constraint solver Minion. We demonstrate that the metamorphic testing method is very effective for finding artificial bugs introduced by random code mutation.
Metadata
Item Type: | Proceedings Paper |
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Copyright, Publisher and Additional Information: | © Springer Nature Switzerland AG 2018. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details. Funding: EPSRC EP/P015638/1 and EP/P026842/1. Dr Jefferson holds a Royal Society University Research Fellowship. |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Depositing User: | Pure (York) |
Date Deposited: | 25 Jan 2019 15:30 |
Last Modified: | 11 Feb 2025 00:06 |
Published Version: | https://doi.org/10.1007/978-3-319-98334-9_46 |
Status: | Published |
Publisher: | Springer |
Series Name: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Identification Number: | 10.1007/978-3-319-98334-9_46 |
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Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:141633 |