Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/94340
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dc.contributorDepartment of Computingen_US
dc.creatorChen, Len_US
dc.creatorPei, Yen_US
dc.creatorFuria, CAen_US
dc.date.accessioned2022-08-11T02:02:43Z-
dc.date.available2022-08-11T02:02:43Z-
dc.identifier.issn0098-5589en_US
dc.identifier.urihttp://hdl.handle.net/10397/94340-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rights© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
dc.rightsThe following publication Chen, L., Pei, Y., & Furia, C. A. (2021). Contract-based program repair without the contracts: An extended study. IEEE Transactions on Software Engineering, 47(12), 2841-2857 is available at https://doi.org/10.1109/TSE.2020.2970009en_US
dc.titleContract-based program repair without the contracts : an extended studyen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage2841en_US
dc.identifier.epage2857en_US
dc.identifier.volume47en_US
dc.identifier.issue12en_US
dc.identifier.doi10.1109/TSE.2020.2970009en_US
dcterms.abstractMost techniques for automated program repair (APR) use tests to drive the repair process; this makes them prone to generating spurious repairs that overfit the available tests unless additional information about expected program behavior is available. Our previous work on Jaid, an APR technique for Java programs, showed that constructing detailed state abstractions - similar to those employed by techniques for programs with contracts - from plain Java code without any special annotations provides valuable additional information, and hence helps mitigate the overfitting problem. This paper extends the work on Jaid with a comprehensive experimental evaluation involving 693 bugs in three different benchmark suites. The evaluation shows, among other things, that: 1) Jaid is effective: it produced correct fixes for over 15 percent of all bugs, with a precision of nearly 60 percent; 2) Jaid is reasonably efficient: on average, it took less than 30 minutes to output a correct fix; 3) Jaid is competitive with the state of the art, as it fixed more bugs than any other technique, and 11 bugs that no other tool can fix; 4) Jaid is robust: its heuristics are complementary and their effectiveness does not depend on the fine-tuning of parameters. The experimental results also indicate the main trade-offs involved in designing an APR technique based on tests, as well as possible directions for further progress in this line of work.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIEEE transactions on software engineering, 1 Dec. 2021, v. 47, no. 12, p. 2841-2857en_US
dcterms.isPartOfIEEE transactions on software engineeringen_US
dcterms.issued2021-12-01-
dc.identifier.scopus2-s2.0-85079458432-
dc.identifier.eissn1939-3520en_US
dc.description.validate202208 bckwen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumbera1666-
dc.identifier.SubFormID45771-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextthe Hong Kong Polytechnic University internal fund; Swiss National Science Foundationen_US
dc.description.pubStatusPublisheden_US
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