{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,5]],"date-time":"2026-02-05T11:15:28Z","timestamp":1770290128049,"version":"3.49.0"},"publisher-location":"New York, NY, USA","reference-count":64,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,4,14]],"date-time":"2024-04-14T00:00:00Z","timestamp":1713052800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,4,14]]},"DOI":"10.1145\/3639477.3639717","type":"proceedings-article","created":{"date-parts":[[2024,5,31]],"date-time":"2024-05-31T13:27:26Z","timestamp":1717162046000},"page":"275-286","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["On the Costs and Benefits of Adopting Lifelong Learning for Software Analytics - Empirical Study on Brown Build and Risk Prediction"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3285-1884","authenticated-orcid":false,"given":"Doriane","family":"Olewicki","sequence":"first","affiliation":[{"name":"Queen's University, Kingston, Ontario, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5989-1413","authenticated-orcid":false,"given":"Sarra","family":"Habchi","sequence":"additional","affiliation":[{"name":"Ubisoft, Montreal, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5248-237X","authenticated-orcid":false,"given":"Mathieu","family":"Nayrolles","sequence":"additional","affiliation":[{"name":"Ubisoft, Montreal, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-7197-846X","authenticated-orcid":false,"given":"Mojtaba","family":"Faramarzi","sequence":"additional","affiliation":[{"name":"Universite de Montreal, Montreal, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9678-2830","authenticated-orcid":false,"given":"Sarath","family":"Chandar","sequence":"additional","affiliation":[{"name":"Polytechnique Montreal, Montreal, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7213-4006","authenticated-orcid":false,"given":"Bram","family":"Adams","sequence":"additional","affiliation":[{"name":"Queen's University, Kingston, Ontario, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2024,5,31]]},"reference":[{"key":"e_1_3_2_1_1_1","first-page":"1572","volume-title":"IEEE","author":"Alshammari A.","year":"2021","unstructured":"A. Alshammari, C. Morris, M. Hilton, and J. Bell, \"Flakeflagger: Predicting flakiness without rerunning tests,\" in 2021 IEEE\/ACM 43rd International Conference on Software Engineering (ICSE). IEEE, 2021, pp. 1572--1584."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF00116828"},{"key":"e_1_3_2_1_3_1","first-page":"134","article-title":"Streamai: Dealing with challenges of continual learning systems for serving ai in production,\" in 2023 IEEE\/ACM 45th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP)","author":"Barry M.","year":"2023","unstructured":"M. Barry, A. Bifet, and J.-L. Billy, \"Streamai: Dealing with challenges of continual learning systems for serving ai in production,\" in 2023 IEEE\/ACM 45th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP). IEEE, 2023, pp. 134--137.","journal-title":"IEEE"},{"key":"e_1_3_2_1_4_1","first-page":"433","volume-title":"IEEE","author":"Bell J.","year":"2018","unstructured":"J. Bell, O. Legunsen, M. Hilton, L. Eloussi, T. Yung, and D. Marinov, \"Deflaker: Automatically detecting flaky tests,\" in 2018 IEEE\/ACM 40th International Conference on Software Engineering (ICSE). IEEE, 2018, pp. 433--444."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1038\/nn.4401"},{"key":"e_1_3_2_1_6_1","volume-title":"Machine learning climate model dynamics: Offline versus online performance,\" arXiv preprint arXiv:2011.03081","author":"Brenowitz N. D.","year":"2020","unstructured":"N. D. Brenowitz, B. Henn, J. McGibbon, S. K. Clark, A. Kwa, W. A. Perkins, O. Watt-Meyer, and C. S. Bretherton, \"Machine learning climate model dynamics: Offline versus online performance,\" arXiv preprint arXiv:2011.03081, 2020."},{"key":"e_1_3_2_1_7_1","first-page":"666","volume-title":"IEEE","author":"Cabral G. G.","year":"2019","unstructured":"G. G. Cabral, L. L. Minku, E. Shihab, and S. Mujahid, \"Class imbalance evolution and verification latency in just-in-time software defect prediction,\" in 2019 IEEE\/ACM 41st International Conference on Software Engineering (ICSE). IEEE, 2019, pp. 666--676."},{"key":"e_1_3_2_1_8_1","article-title":"Towards reliable online just-in-time software defect prediction","author":"Cabral G. G.","year":"2022","unstructured":"G. G. Cabral and L. L. Minku, \"Towards reliable online just-in-time software defect prediction,\" IEEE Transactions on Software Engineering, 2022.","journal-title":"IEEE Transactions on Software Engineering"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"e_1_3_2_1_10_1","volume-title":"Cho et al., \"Xgboost: extreme gradient boosting,\" R package version 0.4-2","author":"Chen T.","unstructured":"T. Chen, T. He, M. Benesty, V. Khotilovich, Y. Tang, H. Cho et al., \"Xgboost: extreme gradient boosting,\" R package version 0.4-2, vol. 1, no. 4, pp. 1--4, 2015."},{"issue":"1","key":"e_1_3_2_1_11_1","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1109\/TFUZZ.2008.2006620","article-title":"From minimum enclosing ball to fast fuzzy inference system training on large datasets","volume":"17","author":"Chung F.-L.","year":"2008","unstructured":"F.-L. Chung, Z. Deng, and S. Wang, \"From minimum enclosing ball to fast fuzzy inference system training on large datasets,\" IEEE Transactions on Fuzzy Systems, vol. 17, no. 1, pp. 173--184, 2008.","journal-title":"IEEE Transactions on Fuzzy Systems"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2016.2616306"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.5555\/579736"},{"key":"e_1_3_2_1_14_1","volume-title":"Incremental learning of concept drift from streaming imbalanced data,\" IEEE transactions on knowledge and data engineering","author":"Ditzler G.","unstructured":"G. Ditzler and R. Polikar, \"Incremental learning of concept drift from streaming imbalanced data,\" IEEE transactions on knowledge and data engineering, vol. 25, no. 10, pp. 2283--2301, 2012."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/MCI.2015.2471196"},{"key":"e_1_3_2_1_16_1","volume-title":"Concurrency-related flaky test detection in android apps,\" arXiv preprint arXiv:2005.10762","author":"Dong Z.","year":"2020","unstructured":"Z. Dong, A. Tiwari, X. L. Yu, and A. Roychoudhury, \"Concurrency-related flaky test detection in android apps,\" arXiv preprint arXiv:2005.10762, 2020."},{"key":"e_1_3_2_1_17_1","first-page":"51","volume-title":"IEEE","author":"Ekanayake J.","year":"2009","unstructured":"J. Ekanayake, J. Tappolet, H. C. Gall, and A. Bernstein, \"Tracking concept drift of software projects using defect prediction quality,\" in 2009 6th IEEE International Working Conference on Mining Software Repositories. IEEE, 2009, pp. 51--60."},{"key":"e_1_3_2_1_18_1","volume-title":"Search on the replay buffer: Bridging planning and reinforcement learning,\" arXiv preprint arXiv:1906.05253","author":"Eysenbach B.","year":"2019","unstructured":"B. Eysenbach, R. Salakhutdinov, and S. Levine, \"Search on the replay buffer: Bridging planning and reinforcement learning,\" arXiv preprint arXiv:1906.05253, 2019."},{"key":"e_1_3_2_1_19_1","volume-title":"Captum python library. Accessed","author":"Facebook Inc.","year":"2023","unstructured":"Facebook Inc. Captum python library. Accessed October 2023. [Online]. Available: https:\/\/captum.ai\/"},{"key":"e_1_3_2_1_20_1","first-page":"87","volume-title":"an empirical study of travis ci,\" in Proceedings of the 33rd ACM\/IEEE International Conference on Automated Software Engineering","author":"Gallaba K.","year":"2018","unstructured":"K. Gallaba, C. Macho, M. Pinzger, and S. McIntosh, \"Noise and heterogeneity in historical build data: an empirical study of travis ci,\" in Proceedings of the 33rd ACM\/IEEE International Conference on Automated Software Engineering, 2018, pp. 87--97."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/2523813"},{"key":"e_1_3_2_1_22_1","volume-title":"Keeping pace with ever-increasing data: Towards continual learning of code intelligence models,\" arXiv preprint arXiv:2302.03482","author":"Gao S.","year":"2023","unstructured":"S. Gao, H. Zhang, C. Gao, and C. Wang, \"Keeping pace with ever-increasing data: Towards continual learning of code intelligence models,\" arXiv preprint arXiv:2302.03482, 2023."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1352-2310(97)00447-0"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2019.2941880"},{"key":"e_1_3_2_1_25_1","volume-title":"Practical MLOps. \" O'Reilly Media","author":"Gift N.","year":"2021","unstructured":"N. Gift and A. Deza, Practical MLOps. \" O'Reilly Media, Inc.\", 2021."},{"key":"e_1_3_2_1_26_1","volume-title":"Gitlab website. Accessed","author":"V.","year":"2023","unstructured":"GitLab B.V. Gitlab website. Accessed October 2023. [Online]. Available: https:\/\/about.gitlab.com\/"},{"key":"e_1_3_2_1_27_1","volume-title":"An empirical investigation of catastrophic forgetting in gradient-based neural networks,\" arXiv preprint arXiv:1312.6211","author":"Goodfellow I. J.","year":"2013","unstructured":"I. J. Goodfellow, M. Mirza, D. Xiao, A. Courville, and Y. Bengio, \"An empirical investigation of catastrophic forgetting in gradient-based neural networks,\" arXiv preprint arXiv:1312.6211, 2013."},{"key":"e_1_3_2_1_28_1","volume-title":"Graphviz website. Accessed","year":"2023","unstructured":"Graphviz. Graphviz website. Accessed October 2023. [Online]. Available: https:\/\/graphviz.org\/"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"crossref","unstructured":"G. Haben S. Habchi M. Papadakis M. Cordy and Y. Le Traon \"A replication study on the usability of code vocabulary in predicting flaky tests \" in 2021 IEEE\/ACM 18th International Conference on Mining Software Repositories (MSR) 2021 pp. 219--229.","DOI":"10.1109\/MSR52588.2021.00034"},{"key":"e_1_3_2_1_30_1","first-page":"39","volume-title":"Empirically detecting false test alarms using association rules,\" in 2015 IEEE\/ACM 37th IEEE International Conference on Software Engineering","author":"Herzig K.","year":"2015","unstructured":"K. Herzig and N. Nagappan, \"Empirically detecting false test alarms using association rules,\" in 2015 IEEE\/ACM 37th IEEE International Conference on Software Engineering, vol. 2. IEEE, 2015, pp. 39--48."},{"key":"e_1_3_2_1_31_1","volume-title":"Selective experience replay for lifelong learning,\" in Proceedings of the AAAI Conference on Artificial Intelligence","author":"Isele D.","unstructured":"D. Isele and A. Cosgun, \"Selective experience replay for lifelong learning,\" in Proceedings of the AAAI Conference on Artificial Intelligence, vol. 32, no. 1, 2018."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2012.70"},{"key":"e_1_3_2_1_33_1","volume-title":"Measuring catastrophic forgetting in neural networks,\" in Proceedings of the AAAI Conference on Artificial Intelligence","author":"Kemker R.","unstructured":"R. Kemker, M. McClure, A. Abitino, T. Hayes, and C. Kanan, \"Measuring catastrophic forgetting in neural networks,\" in Proceedings of the AAAI Conference on Artificial Intelligence, vol. 32, no. 1, 2018."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1611835114"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"crossref","unstructured":"J. Lampel S. Just S. Apel and A. Zeller \"When life gives you oranges: detecting and diagnosing intermittent job failures at mozilla \" in Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering 2021 pp. 1381--1392.","DOI":"10.1145\/3468264.3473931"},{"key":"e_1_3_2_1_36_1","volume-title":"Archer: Aggressive rewards to counter bias in hindsight experience replay,\" arXiv preprint arXiv:1809.02070","author":"Lanka S.","year":"2018","unstructured":"S. Lanka and T. Wu, \"Archer: Aggressive rewards to counter bias in hindsight experience replay,\" arXiv preprint arXiv:1809.02070, 2018."},{"key":"e_1_3_2_1_37_1","first-page":"661","volume-title":"Efficient mini-batch training for stochastic optimization,\" in Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining","author":"Li M.","year":"2014","unstructured":"M. Li, T. Zhang, Y. Chen, and A. J. Smola, \"Efficient mini-batch training for stochastic optimization,\" in Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, 2014, pp. 661--670."},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11704-016-6903-6"},{"issue":"12","key":"e_1_3_2_1_39_1","first-page":"2346","article-title":"Learning under concept drift: A review","volume":"31","author":"Lu J.","year":"2018","unstructured":"J. Lu, A. Liu, F. Dong, F. Gu, J. Gama, and G. Zhang, \"Learning under concept drift: A review,\" IEEE Transactions on Knowledge and Data Engineering, vol. 31, no. 12, pp. 2346--2363, 2018.","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3360578"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"crossref","unstructured":"D. Marijan \"Comparative study of machine learning test case prioritization for continuous integration testing \" arXiv preprint arXiv:2204.10899 2022.","DOI":"10.2139\/ssrn.4105089"},{"key":"e_1_3_2_1_42_1","first-page":"560","volume-title":"Are fix-inducing changes a moving target? a longitudinal case study of just-in-time defect prediction,\" in Proceedings of the 40th International Conference on Software Engineering","author":"McIntosh S.","year":"2018","unstructured":"S. McIntosh and Y. Kamei, \"Are fix-inducing changes a moving target? a longitudinal case study of just-in-time defect prediction,\" in Proceedings of the 40th International Conference on Software Engineering, 2018, pp. 560--560."},{"key":"e_1_3_2_1_43_1","first-page":"181","volume-title":"A comparative analysis of the efficiency of change metrics and static code attributes for defect prediction,\" in Proceedings of the 30th international conference on Software engineering","author":"Moser R.","year":"2008","unstructured":"R. Moser, W. Pedrycz, and G. Succi, \"A comparative analysis of the efficiency of change metrics and static code attributes for defect prediction,\" in Proceedings of the 30th international conference on Software engineering, 2008, pp. 181--190."},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"crossref","unstructured":"M. Nayrolles and A. Hamou-Lhadj \"Clever: combining code metrics with clone detection for just-in-time fault prevention and resolution in large industrial projects \" in Proceedings of the 15th International Conference on Mining Software Repositories 2018 pp. 153--164.","DOI":"10.1145\/3196398.3196438"},{"key":"e_1_3_2_1_45_1","volume-title":"Towards language-independent brown build detection","author":"Olewicki D.","year":"2022","unstructured":"D. Olewicki, M. Nayrolles, and B. Adams, \"Towards language-independent brown build detection,\" 2022."},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2019.01.012"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2017.09.001"},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0211359"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-39940-9_565"},{"issue":"01","key":"e_1_3_2_1_50_1","doi-asserted-by":"crossref","first-page":"1352","DOI":"10.1609\/aaai.v33i01.33011352","article-title":"Scalable recollections for continual lifelong learning","volume":"33","author":"Riemer M.","year":"2019","unstructured":"M. Riemer, T. Klinger, D. Bouneffouf, and M. Franceschini, \"Scalable recollections for continual lifelong learning,\" in Proceedings of the AAAI Conference on Artificial Intelligence, vol. 33, no. 01, 2019, pp. 1352--1359.","journal-title":"Proceedings of the AAAI Conference on Artificial Intelligence"},{"key":"e_1_3_2_1_51_1","first-page":"966","volume-title":"Commit guru: analytics and risk prediction of software commits,\" in Proceedings of the 2015 10th joint meeting on foundations of software engineering","author":"Rosen C.","year":"2015","unstructured":"C. Rosen, B. Grawi, and E. Shihab, \"Commit guru: analytics and risk prediction of software commits,\" in Proceedings of the 2015 10th joint meeting on foundations of software engineering, 2015, pp. 966--969."},{"issue":"1","key":"e_1_3_2_1_52_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10515-021-00319-5","article-title":"Improving the prediction of continuous integration build failures using deep learning","volume":"29","author":"Saidani I.","year":"2022","unstructured":"I. Saidani, A. Ouni, and M. W. Mkaouer, \"Improving the prediction of continuous integration build failures using deep learning,\" Automated Software Engineering, vol. 29, no. 1, pp. 1--61, 2022.","journal-title":"Automated Software Engineering"},{"key":"e_1_3_2_1_53_1","volume-title":"Continuous delivery for machine learning: Automating the end-to-end lifecycle of machine learning applications","author":"Sato D.","year":"2019","unstructured":"D. Sato, A. Wider, and C. Windheuser, \"Continuous delivery for machine learning: Automating the end-to-end lifecycle of machine learning applications,\" 2019. [Online]. Available: https:\/\/martinfowler.com\/articles\/cd4ml.html"},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"crossref","first-page":"476","DOI":"10.1145\/3387940.3391489","article-title":"Improving code recommendations by combining neural and classical machine learning approaches","author":"Schumacher M. E. H.","year":"2020","unstructured":"M. E. H. Schumacher, K. T. Le, and A. Andrzejak, \"Improving code recommendations by combining neural and classical machine learning approaches,\" in Proceedings of the IEEE\/ACM 42nd International Conference on Software Engineering Workshops, 2020, pp. 476--482.","journal-title":"Proceedings of the IEEE\/ACM 42nd International Conference on Software Engineering Workshops"},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2017.2685629"},{"key":"e_1_3_2_1_56_1","first-page":"1","volume-title":"An industrial study on the risk of software changes,\" in Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering","author":"Shihab E.","year":"2012","unstructured":"E. Shihab, A. E. Hassan, B. Adams, and Z. M. Jiang, \"An industrial study on the risk of software changes,\" in Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering, 2012, pp. 1--11."},{"key":"e_1_3_2_1_57_1","first-page":"554","volume-title":"IEEE","author":"Tabassum S.","year":"2020","unstructured":"S. Tabassum, L. L. Minku, D. Feng, G. G. Cabral, and L. Song, \"An investigation of cross-project learning in online just-in-time software defect prediction,\" in 2020 IEEE\/ACM 42nd International Conference on Software Engineering (ICSE). IEEE, 2020, pp. 554--565."},{"key":"e_1_3_2_1_58_1","first-page":"99","volume-title":"IEEE","author":"Tan M.","year":"2015","unstructured":"M. Tan, L. Tan, S. Dara, and C. Mayeux, \"Online defect prediction for imbalanced data,\" in 2015 IEEE\/ACM 37th IEEE International Conference on Software Engineering, vol. 2. IEEE, 2015, pp. 99--108."},{"key":"e_1_3_2_1_59_1","first-page":"486","volume-title":"IEEE","author":"Thuijsman S.","year":"2019","unstructured":"S. Thuijsman, D. Hendriks, R. Theunissen, M. Reniers, and R. Schiffelers, \"Computational effort of bdd-based supervisor synthesis of extended finite automata,\" in 2019 IEEE 15th International Conference on Automation Science and Engineering (CASE). IEEE, 2019, pp. 486--493."},{"key":"e_1_3_2_1_60_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.catena.2016.06.004"},{"key":"e_1_3_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10664-011-9182-8"},{"key":"e_1_3_2_1_62_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.websem.2011.05.003"},{"key":"e_1_3_2_1_63_1","doi-asserted-by":"crossref","first-page":"964","DOI":"10.1007\/s10618-015-0448-4","article-title":"Characterizing concept drift","author":"Webb G.","year":"2016","unstructured":"G. Webb, R. Hypde, H. Cao, H. L. Nguyen, and F. Petitjean, \"Characterizing concept drift,\" in Data Mining and Knowledge Discovery, 2016, pp. 964--994.","journal-title":"Data Mining and Knowledge Discovery"},{"key":"e_1_3_2_1_64_1","doi-asserted-by":"publisher","DOI":"10.5555\/560438"}],"event":{"name":"ICSE-SEIP '24: 46th International Conference on Software Engineering: Software Engineering in Practice","location":"Lisbon Portugal","acronym":"ICSE-SEIP '24","sponsor":["SIGSOFT ACM Special Interest Group on Software Engineering","IEEE CS","Faculty of Engineering of University of Porto"]},"container-title":["Proceedings of the 46th International Conference on Software Engineering: Software Engineering in Practice"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3639477.3639717","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3639477.3639717","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T23:44:31Z","timestamp":1750290271000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3639477.3639717"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,4,14]]},"references-count":64,"alternative-id":["10.1145\/3639477.3639717","10.1145\/3639477"],"URL":"https:\/\/doi.org\/10.1145\/3639477.3639717","relation":{},"subject":[],"published":{"date-parts":[[2024,4,14]]},"assertion":[{"value":"2024-05-31","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}