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dc.contributor.authorAkgun, Ozgur
dc.contributor.authorGent, Ian Philip
dc.contributor.authorJefferson, Christopher Anthony
dc.contributor.authorMiguel, Ian James
dc.contributor.authorNightingale, Peter William
dc.contributor.editorHooker, John
dc.identifier.citationAkgun , O , Gent , I P , Jefferson , C A , Miguel , I J & Nightingale , P W 2018 , Metamorphic testing of constraint solvers . in J Hooker (ed.) , Principles and Practice of Constraint Programming : 24th International Conference, CP 2018, Lille, France, August 27-31, 2018, Proceedings . Lecture Notes in Computer Science , vol. 11008 , Springer , pp. 727-736 , 24th International Conference on Principles and Practice of Constraint Programming (CP 2018) , Lille , France , 27/08/18 .
dc.identifier.otherPURE: 253604924
dc.identifier.otherPURE UUID: 53282bba-e208-4f9a-b816-728d0a72fd7b
dc.identifier.otherScopus: 85053168572
dc.identifier.otherORCID: /0000-0002-5052-8634/work/47928953
dc.identifier.otherORCID: /0000-0001-9519-938X/work/47928987
dc.identifier.otherORCID: /0000-0003-2979-5989/work/60887573
dc.identifier.otherORCID: /0000-0002-6930-2686/work/68281466
dc.identifier.otherWOS: 000546520500046
dc.descriptionFunding: EPSRC EP/P015638/1 and EP/P026842/1. Dr Jefferson holds a Royal Society University Research Fellowship.en
dc.description.abstractConstraint 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.
dc.relation.ispartofPrinciples and Practice of Constraint Programmingen
dc.relation.ispartofseriesLecture Notes in Computer Scienceen
dc.rights© 2018, Springer Nature Switzerland. This work has been made available online in accordance with the publisher’s policies. This is the author created accepted version manuscript following peer review and as such may differ slightly from the final published version. The final published version of this work is available at _ 46 _ 1en
dc.subjectQA75 Electronic computers. Computer scienceen
dc.titleMetamorphic testing of constraint solversen
dc.typeConference itemen
dc.contributor.sponsorThe Royal Societyen
dc.contributor.institutionUniversity of St Andrews. School of Computer Scienceen
dc.contributor.institutionUniversity of St Andrews. Centre for Interdisciplinary Research in Computational Algebraen

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