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Hence, efficiently constructing high-quality mutation faults is critical. To address the effectiveness limitations of traditional and deep learning-based mutation techniques, we first proposed\n            <jats:monospace>LEAM<\/jats:monospace>\n            , utilizing a syntax-guided encoder\u2013decoder architecture with extended grammar rules. While\n            <jats:monospace>LEAM<\/jats:monospace>\n            significantly enhances the effectiveness, it does not consider the associated testing cost. To further improve the efficiency of\n            <jats:monospace>LEAM<\/jats:monospace>\n            , we propose\n            <jats:monospace>LEAM++<\/jats:monospace>\n            , adopting a novel selective mutation fault construction module based on the probability of grammar rule sequences and the similarity of mutation faults.\n          <\/jats:p>\n          <jats:p>\n            We extensively evaluate\n            <jats:monospace>LEAM++<\/jats:monospace>\n            using Defects4J. Regarding effectiveness, the results demonstrate that the mutation faults constructed by\n            <jats:monospace>LEAM++<\/jats:monospace>\n            can better represent real faults than two traditional techniques (\n            <jats:monospace>Major<\/jats:monospace>\n            and\n            <jats:monospace>PIT<\/jats:monospace>\n            ) and the deep learning-based technique (\n            <jats:monospace>DeepMutation<\/jats:monospace>\n            ), and substantially boost three downstream applications, i.e., mutation-based test case prioritization, mutation-based fault localization, and mutation-based bug detection. Regarding efficiency,\n            <jats:monospace>LEAM++<\/jats:monospace>\n            demonstrates superiority over the four selective mutation testing techniques across three scenarios, i.e., mutation testing, mutation-based test case prioritization, and mutation-based fault localization. Our work serves as an important step toward the efficiently automated construction of mutation faults.\n          <\/jats:p>","DOI":"10.1145\/3725528","type":"journal-article","created":{"date-parts":[[2025,3,21]],"date-time":"2025-03-21T11:00:29Z","timestamp":1742554829000},"page":"1-41","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["LEAM++: Learning for Selective Mutation Fault Construction"],"prefix":"10.1145","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9316-7250","authenticated-orcid":false,"given":"Zhao","family":"Tian","sequence":"first","affiliation":[{"name":"College of Intelligence and Computing, Tianjin University, Tianjin, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3056-9962","authenticated-orcid":false,"given":"Junjie","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Intelligence and Computing, Tianjin University, Tianjin, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2004-0902","authenticated-orcid":false,"given":"Dong","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Intelligence and Computing, Tianjin University, Tianjin, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8036-2623","authenticated-orcid":false,"given":"Qihao","family":"Zhu","sequence":"additional","affiliation":[{"name":"Key Laboratory of HCST, MoE DCST, Peking University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-4680-6012","authenticated-orcid":false,"given":"Xingyu","family":"Fan","sequence":"additional","affiliation":[{"name":"College of Intelligence and Computing, Tianjin University, Tianjin, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5175-2702","authenticated-orcid":false,"given":"Lingming","family":"Zhang","sequence":"additional","affiliation":[{"name":"University of Illinois Urbana-Champaign, Urbana, Illinois, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,10,4]]},"reference":[{"key":"e_1_3_1_2_2","unstructured":"tianzhaotju\/LEAM. 2024. 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