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dc.contributor.authorPatrick, Matthewen
dc.contributor.authorCraig, Andrewen
dc.contributor.authorCunniffe, Niken
dc.contributor.authorParry, Matthewen
dc.contributor.authorGilligan, Christopheren
dc.date.accessioned2016-06-03T11:19:55Z
dc.date.available2016-06-03T11:19:55Z
dc.date.issued2016-07-18en
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/256153
dc.description.abstractStochastic models can be difficult to test due to their complexity and randomness, yet their predictions are often used to make important decisions, so they need to be correct. We introduce a new search-based technique for testing implementations of stochastic models by maximising the differences between the implementation and a pseudo-oracle. Our technique reduces testing effort and enables discrepancies to be found that might otherwise be overlooked. We show the technique can identify differences challenging for humans to observe, and use it to help a new user understand implementation differences in a real model of a citrus disease (Huanglongbing) used to inform policy and research.
dc.description.sponsorshipWellcome Trust
dc.languageEnglishen
dc.language.isoenen
dc.publisherAssociation for Computing Machinery
dc.subjectcomputational modelsen
dc.subjecttestingen
dc.subjectsearch-based optimisationen
dc.titleTesting stochastic software using pseudo-oraclesen
dc.typeConference Object
dc.description.versionThis is the author accepted manuscript. The final version is available from the Association for Computing Machinery via http://dx.doi.org/10.1145/2931037.2931063en
prism.endingPage246
prism.publicationDate2016en
prism.publicationNameISSTA 2016 Proceedings of the 25th International Symposium on Software Testing and Analysisen
prism.startingPage235
dc.identifier.doi10.17863/CAM.94
dcterms.dateAccepted2016-04-17en
rioxxterms.versionofrecord10.1145/2931037.2931063en
rioxxterms.versionAMen
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2016-07-18en
dc.contributor.orcidCraig, Andrew [0000-0003-1144-2982]
dc.contributor.orcidCunniffe, Nik [0000-0002-3533-8672]
dc.contributor.orcidGilligan, Christopher [0000-0002-6845-0003]
rioxxterms.typeConference Paper/Proceeding/Abstracten


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