{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T07:39:07Z","timestamp":1723016347603},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,7]]},"abstract":"<jats:p>Genetic programming is an effective technique for inductive synthesis of programs from tests, i.e. training examples of desired input-output behavior. Programs synthesized in this way are not guaranteed to generalize beyond the training set, which is unacceptable in many applications. We present Counterexample-Driven Genetic Programming (CDGP) that employs evolutionary search to synthesize provably correct programs from formal specifications. CDGP employs a Satisfiability Modulo Theories (SMT) solver to formally verify programs in the evaluation phase. A failed verification produces counterexamples that are in turn used to calculate fitness and thereby drive the search process. When compared with a range of approaches on a suite of state-of-the-art specification-based synthesis benchmarks, CDGP systematically outperforms them, typically synthesizing correct programs faster and using fewer tests.<\/jats:p>","DOI":"10.24963\/ijcai.2018\/742","type":"proceedings-article","created":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T01:49:10Z","timestamp":1530755350000},"page":"5304-5308","source":"Crossref","is-referenced-by-count":4,"title":["Counterexample-Driven Genetic Programming: Stochastic Synthesis of Provably Correct Programs"],"prefix":"10.24963","author":[{"given":"Krzysztof","family":"Krawiec","sequence":"first","affiliation":[{"name":"Poznan University of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Iwo","family":"B\u0142\u0105dek","sequence":"additional","affiliation":[{"name":"Poznan University of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jerry","family":"Swan","sequence":"additional","affiliation":[{"name":"University of York"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John H.","family":"Drake","sequence":"additional","affiliation":[{"name":"Queen Mary University of London"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"number":"27","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-2018","name":"Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}","start":{"date-parts":[[2018,7,13]]},"theme":"Artificial Intelligence","location":"Stockholm, Sweden","end":{"date-parts":[[2018,7,19]]}},"container-title":["Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T01:55:40Z","timestamp":1530755740000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2018\/742"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2018,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2018\/742","relation":{},"subject":[],"published":{"date-parts":[[2018,7]]}}}