{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T19:10:38Z","timestamp":1782846638715,"version":"3.54.5"},"reference-count":77,"publisher":"Association for Computing Machinery (ACM)","issue":"FSE","license":[{"start":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T00:00:00Z","timestamp":1782777600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["92582201"],"award-info":[{"award-number":["92582201"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002920","name":"Research Grants Council, University Grants Committee","doi-asserted-by":"publisher","award":["16206524"],"award-info":[{"award-number":["16206524"]}],"id":[{"id":"10.13039\/501100002920","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. ACM Softw. Eng."],"published-print":{"date-parts":[[2026,6,30]]},"abstract":"<jats:p>Metamorphic testing (MT) is a widely recognized technique for alleviating the oracle problem in software testing. However, its adoption is hindered by the difficulty of constructing effective metamorphic relations (MRs), which often require domain-specific or hard-to-obtain knowledge. In this work, we propose a novel approach that leverages the functional coupling between methods, which is readily available in source code, to automatically construct MRs and generate metamorphic test cases (MTCs). Our technique, MR-Coupler, identifies functionally coupled method pairs, employs large language models to generate candidate MTCs, and validates them through test amplification and mutation analysis. In particular, we leverage three functional coupling features to avoid expensive enumeration of possible method pairs, and a novel validation mechanism to reduce false alarms. Our evaluation of MR-Coupler on 100 human-written MTCs and 50 real-world bugs shows that it generates valid MTCs for over 90% of tasks, improves valid MTC generation by 64.90%, and reduces false alarms by 36.56% compared to baselines. Furthermore, the MTCs generated by MR-Coupler detect 44% of the real bugs. Our results highlight the effectiveness of leveraging functional coupling for automated MR construction and the potential of MR-Coupler to facilitate the adoption of MT in practice. We also released the tool and experimental data to support future research.<\/jats:p>","DOI":"10.1145\/3808213","type":"journal-article","created":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T17:06:14Z","timestamp":1782839174000},"page":"4690-4713","source":"Crossref","is-referenced-by-count":0,"title":["MR-Coupler: Automated Metamorphic Test Generation via Functional Coupling Analysis"],"prefix":"10.1145","volume":"3","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-2887-1690","authenticated-orcid":false,"given":"Congying","family":"Xu","sequence":"first","affiliation":[{"name":"The Hong Kong University of Science and Technology, Hong Kong, China"},{"name":"Guangzhou HKUST Fok Ying Tung Research Institute, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3082-5957","authenticated-orcid":false,"given":"Hengcheng","family":"Zhu","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology, Hong Kong, China"},{"name":"Guangzhou HKUST Fok Ying Tung Research Institute, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1220-8728","authenticated-orcid":false,"given":"Songqiang","family":"Chen","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology, Hong Kong, China"},{"name":"Guangzhou HKUST Fok Ying Tung Research Institute, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6126-303X","authenticated-orcid":false,"given":"Jiarong","family":"Wu","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology, Hong Kong, China"},{"name":"Guangzhou HKUST Fok Ying Tung Research Institute, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5885-9297","authenticated-orcid":false,"given":"Valerio","family":"Terragni","sequence":"additional","affiliation":[{"name":"University of Auckland, Auckland, New Zealand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3508-7172","authenticated-orcid":false,"given":"Shing-Chi","family":"Cheung","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology, Hong Kong, China"},{"name":"Guangzhou HKUST Fok Ying Tung Research Institute, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,6,30]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Alibaba. 2025. Qwen3-coder. Retrieved September 1 2025 from https:\/\/qwenlm.github.io\/blog\/qwen3-coder\/"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/SCAM.2010.25"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3729398"},{"key":"e_1_2_1_4_1","volume-title":"Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering. ACM, 1264-1274","author":"Ayerdi Jon","year":"2021","unstructured":"Jon Ayerdi, Valerio Terragni, Aitor Arrieta, Paolo Tonella, Goiuria Sagardui, and Maite Arratibel. 2021. Generating metamorphic relations for cyber-physical systems with genetic programming: an industrial case study. In Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering. ACM, 1264-1274."},{"key":"e_1_2_1_5_1","volume-title":"GenMorph: Automatically Generating Metamorphic Relations via Genetic Programming","author":"Ayerdi Jon","year":"2024","unstructured":"Jon Ayerdi, Valerio Terragni, Gunel Jahangirova, Aitor Arrieta, and Paolo Tonella. 2024. GenMorph: Automatically Generating Metamorphic Relations via Genetic Programming. IEEE Transactions on Software Engineering (2024), 1-12."},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/J.JSS.2021.111041"},{"key":"e_1_2_1_7_1","volume-title":"Understanding LLM-Driven Test Oracle Generation. In 2025 2nd IEEE\/ACM International Conference on AI-powered Software (AIware). IEEE, 29-39","author":"Bodicoat Adam","year":"2025","unstructured":"Adam Bodicoat, Gunel Jahangirova, and Valerio Terragni. 2025. Understanding LLM-Driven Test Oracle Generation. In 2025 2nd IEEE\/ACM International Conference on AI-powered Software (AIware). IEEE, 29-39."},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3490488"},{"key":"e_1_2_1_9_1","volume-title":"Concerned with Data Contamination? Assessing Countermeasures in Code Language Model. CoRR abs\/2403.16898","author":"Cao Jialun","year":"2024","unstructured":"Jialun Cao, Wuqi Zhang, and Shing-Chi Cheung. 2024. Concerned with Data Contamination? Assessing Countermeasures in Code Language Model. CoRR abs\/2403.16898 (2024). arXiv:2403.16898"},{"key":"e_1_2_1_10_1","volume-title":"International Conference on Automated Software Engineering. IEEE, 104-116","author":"Chen Songqiang","year":"2021","unstructured":"Songqiang Chen, Shuo Jin, and Xiaoyuan Xie. 2021. Testing Your Question Answering Software via Asking Recursively. In International Conference on Automated Software Engineering. IEEE, 104-116."},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3143561"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jss.2015.07.037"},{"key":"e_1_2_1_13_1","volume-title":"ChatUniTest: A Framework for LLM-Based Test Generation. In Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering. 572-576","author":"Chen Yinghao","year":"2024","unstructured":"Yinghao Chen, Zehao Hu, Chen Zhi, Junxiao Han, Shuiguang Deng, and Jianwei Yin. 2024. ChatUniTest: A Framework for LLM-Based Test Generation. In Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering. 572-576."},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/ASE63991.2025.00385"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSME64153.2025.00025"},{"key":"e_1_2_1_16_1","unstructured":"DeepSeek. 2025. DeepSeek-V3.1. Retrieved September 1 2025 from https:\/\/api-docs.deepseek.com\/news\/news250821"},{"key":"e_1_2_1_17_1","unstructured":"Diennea. 2025. SimplerPlannerTest. https:\/\/github.com\/diennea\/herddb\/blob\/master\/herddb-core\/src\/test\/java\/herddb\/ sql\/SimplerPlannerTest.java"},{"key":"e_1_2_1_18_1","first-page":"1","article-title":"Evaluating Large Language Models in Class-Level Code Generation. In nternational Conference on Software Engineering","volume":"81","author":"Du Xueying","year":"2024","unstructured":"Xueying Du, Mingwei Liu, Kaixin Wang, Hanlin Wang, Junwei Liu, Yixuan Chen, Jiayi Feng, Chaofeng Sha, Xin Peng, and Yiling Lou. 2024. Evaluating Large Language Models in Class-Level Code Generation. In nternational Conference on Software Engineering. ACM, 81:1-81:13.","journal-title":"ACM"},{"key":"e_1_2_1_19_1","volume-title":"De-Hallucinator: Iterative Grounding for LLM-Based Code Completion. CoRR abs\/2401.01701","author":"Eghbali Aryaz","year":"2024","unstructured":"Aryaz Eghbali and Michael Pradel. 2024. De-Hallucinator: Iterative Grounding for LLM-Based Code Completion. CoRR abs\/2401.01701 (2024). arXiv:2401.01701"},{"key":"e_1_2_1_20_1","volume-title":"leaderboard. Retrieved","year":"2025","unstructured":"Evalplus. 2025. leaderboard. Retrieved September 1, 2025 from https:\/\/evalplus.github.io\/leaderboard.html"},{"key":"e_1_2_1_21_1","unstructured":"FasterXML. 2025. BasicParserFilteringTest. https:\/\/github.com\/FasterXML\/jackson-core\/blob\/3.x\/src\/test\/java\/tools\/ jackson\/core\/unittest\/filter\/BasicParserFilteringTest.java#L432"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/J.INFSOF.2018.11.008"},{"key":"e_1_2_1_23_1","doi-asserted-by":"crossref","unstructured":"Christoph Hazott and Daniel Gro\u00dfe. 2025. LLM-assisted Metamorphic Testing of Embedded Graphics Libraries. In Forum on Specification and Design Languages. https:\/\/ics.jku.at\/files\/2025FDL_LLM-assisted_Metamorphic_Testing_ of_Embedded_Graphics_Libraries.pdf","DOI":"10.1109\/FDL68117.2025.11165405"},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3611643.3616265"},{"key":"e_1_2_1_25_1","unstructured":"Apache IoTDB. 2025. IoTDB Issue #13691. https:\/\/github.com\/apache\/iotdb\/pull\/13691"},{"key":"e_1_2_1_26_1","unstructured":"JavaParser. 2024. JavaParser. Retrieved June 6 2024 from https:\/\/javaparser.org\/"},{"key":"e_1_2_1_27_1","unstructured":"Jcabi. 2025. GitHub Commit 777a078913. https:\/\/github.com\/jcabi\/jcabi-github\/commit\/777a078913"},{"key":"e_1_2_1_28_1","volume-title":"Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering. 492-496","author":"Jiang Yu","year":"2024","unstructured":"Yu Jiang, Jie Liang, Fuchen Ma, Yuanliang Chen, Chijin Zhou, Yuheng Shen, Zhiyong Wu, Jingzhou Fu, Mingzhe Wang, Shanshan Li, et al. 2024. When fuzzing meets llms: Challenges and opportunities. In Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering. 492-496."},{"key":"e_1_2_1_29_1","unstructured":"Knowledge Cutoff Information of GPT-4o-mini [n. d.]. https:\/\/community.openai.com\/t\/introducing-gpt-4o-mini-inthe-api\/871594"},{"key":"e_1_2_1_30_1","volume-title":"Conference on Programming Language Design and Implementation. ACM, 216-226","author":"Le Vu","year":"2014","unstructured":"Vu Le, Mehrdad Afshari, and Zhendong Su. 2014. Compiler validation via equivalence modulo inputs. In Conference on Programming Language Design and Implementation. ACM, 216-226."},{"key":"e_1_2_1_31_1","volume-title":"CodaMosa: Escaping Coverage Plateaus in Test Generation with Pre-trained Large Language Models. In International Conference on Software Engineering. IEEE, 919-931","author":"Lemieux Caroline","year":"2023","unstructured":"Caroline Lemieux, Jeevana Priya Inala, Shuvendu K. Lahiri, and Siddhartha Sen. 2023. CodaMosa: Escaping Coverage Plateaus in Test Generation with Pre-trained Large Language Models. In International Conference on Software Engineering. IEEE, 919-931."},{"key":"e_1_2_1_32_1","volume-title":"Chain of Code: Reasoning with a Language Model-Augmented Code Emulator. CoRR abs\/2312.04474","author":"Li Chengshu","year":"2023","unstructured":"Chengshu Li, Jacky Liang, Andy Zeng, Xinyun Chen, Karol Hausman, Dorsa Sadigh, Sergey Levine, Li Fei-Fei, Fei Xia, and Brian Ichter. 2023. Chain of Code: Reasoning with a Language Model-Augmented Code Emulator. CoRR abs\/2312.04474 (2023). arXiv:2312.04474"},{"key":"e_1_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/ISSRE66568.2025.00028"},{"key":"e_1_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/ASE63991.2025.00381"},{"key":"e_1_2_1_35_1","unstructured":"Yujia Li David H. Choi Junyoung Chung Nate Kushman Julian Schrittwieser and et al. 2022. Competition-Level Code Generation with AlphaCode. CoRR abs\/2203.07814 (2022). arXiv:2203.07814"},{"key":"e_1_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2013.46"},{"key":"e_1_2_1_37_1","volume-title":"Can ChatGPT Advance Software Testing Intelligence? An Experience Report on Metamorphic Testing. CoRR abs\/2310.19204","author":"Luu Quang-Hung","year":"2023","unstructured":"Quang-Hung Luu, Huai Liu, and Tsong Yueh Chen. 2023. Can ChatGPT Advance Software Testing Intelligence? An Experience Report on Metamorphic Testing. CoRR abs\/2310.19204 (2023). arXiv:2310.19204 https:\/\/arxiv.org\/abs\/2310. 19204"},{"key":"e_1_2_1_38_1","volume-title":"Fuzzing Deep Learning Compilers with HirGen. In International Symposium on Software Testing and Analysis. ACM, 248-260","author":"Ma Haoyang","year":"2023","unstructured":"Haoyang Ma, Qingchao Shen, Yongqiang Tian, Junjie Chen, and Shing-Chi Cheung. 2023. Fuzzing Deep Learning Compilers with HirGen. In International Symposium on Software Testing and Analysis. ACM, 248-260."},{"key":"e_1_2_1_39_1","unstructured":"Major. 2025. Mutation Testing. https:\/\/mutation-testing.org\/"},{"key":"e_1_2_1_40_1","first-page":"450","volume-title":"Proceedings of the ACM on Software Engineering 1, FSE","author":"Nolasco Agust\u00edn","year":"2024","unstructured":"Agust\u00edn Nolasco, Facundo Molina, Renzo Degiovanni, Alessandra Gorla, Diego Garbervetsky, Mike Papadakis, Sebasti\u00e1n Uchitel, Nazareno Aguirre, and Marcelo F. Frias. 2024. Abstraction-Aware Inference of Metamorphic Relations. Proceedings of the ACM on Software Engineering 1, FSE (2024), 450-472."},{"key":"e_1_2_1_41_1","volume-title":"GPT-4o mini. Retrieved","author":"AI.","year":"2025","unstructured":"OpenAI. 2025. GPT-4o mini. Retrieved September 1, 2025 from https:\/\/platform.openai.com\/docs\/models\/gpt-4o-mini"},{"key":"e_1_2_1_42_1","unstructured":"Optimatika. 2025. OjAlgo Issue #49. https:\/\/github.com\/optimatika\/ojAlgo\/issues\/49"},{"key":"e_1_2_1_43_1","volume-title":"OjAlgo Issue #49. Retrieved","year":"2025","unstructured":"Optimatika. 2025. OjAlgo Issue #49. Retrieved September 1, 2025 from https:\/\/github.com\/optimatika\/ojAlgo\/issues\/49"},{"key":"e_1_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1007\/S10664-008-9088-2"},{"key":"e_1_2_1_45_1","volume-title":"2025 IEEE International Conference on Software Maintenance and Evolution (ICSME). IEEE, 930-934","author":"Ravi Ravin","year":"2025","unstructured":"Ravin Ravi, Dylan Bradshaw, Stefano Ruberto, Gunel Jahangirova, and Valerio Terragni. 2025. LLMLOOP: Improving LLM-Generated Code and Tests through Automated Iterative Feedback Loops. In 2025 IEEE International Conference on Software Maintenance and Evolution (ICSME). IEEE, 930-934."},{"key":"e_1_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2023.3334955"},{"key":"e_1_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2016.2532875"},{"key":"e_1_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2017.2764464"},{"key":"e_1_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-70245-"},{"key":"e_1_2_1_50_1","volume-title":"International Conference on Object-Oriented Programming, Systems, Languages, and Applications,. ACM, 849-863","author":"Sun Chengnian","year":"2016","unstructured":"Chengnian Sun, Vu Le, and Zhendong Su. 2016. Finding compiler bugs via live code mutation. In International Conference on Object-Oriented Programming, Systems, Languages, and Applications,. ACM, 849-863."},{"key":"e_1_2_1_51_1","volume-title":"International Workshop on Metamorphic Testing. ACM, 12-18","author":"Sun Chang-Ai","unstructured":"Chang-Ai Sun, Yiqiang Liu, Zuoyi Wang, and W. K. Chan. 2016. \ud835\udf07MT: a data mutation directed metamorphic relation acquisition methodology. In International Workshop on Metamorphic Testing. ACM, 12-18."},{"key":"e_1_2_1_52_1","volume-title":"ChatGPT vs SBST: A Comparative Assessment of Unit Test Suite Generation","author":"Tang Yutian","year":"2024","unstructured":"Yutian Tang, Zhijie Liu, Zhichao Zhou, and Xiapu Luo. 2024. ChatGPT vs SBST: A Comparative Assessment of Unit Test Suite Generation. IEEE Transactions on Software Engineering (2024), 1-19."},{"key":"e_1_2_1_53_1","volume-title":"Evolutionary Improvement of Assertion Oracles. In Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering. 1178-1189","author":"Terragni Valerio","year":"2020","unstructured":"Valerio Terragni, Gunel Jahangirova, Paolo Tonella, and Mauro Pezz\u00e8. 2020. Evolutionary Improvement of Assertion Oracles. In Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering. 1178-1189."},{"key":"e_1_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1145\/3715003"},{"key":"e_1_2_1_55_1","unstructured":"TheAlgorithms. 2025. AESEncryptionTest. https:\/\/github.com\/TheAlgorithms\/Java\/blob\/master\/src\/test\/java\/com\/ thealgorithms\/ciphers\/AESEncryptionTest.java"},{"key":"e_1_2_1_56_1","volume-title":"MR-Coupler website. Retrieved","year":"2025","unstructured":"MR-Coupler. 2025. MR-Coupler website. Retrieved September 2, 2025 from https:\/\/mr-coupler.github.io\/"},{"key":"e_1_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.5281\/zenodo.19438045"},{"key":"e_1_2_1_58_1","volume-title":"Prague, Czech Republic","volume":"335","author":"Tsigkanos Christos","year":"2023","unstructured":"Christos Tsigkanos, Pooja Rani, Sebastian M\u00fcller, and Timo Kehrer. 2023. Variable Discovery with Large Language Models for Metamorphic Testing of Scientific Software. In Computational Science -ICCS 2023 -23rd International Conference, Prague, Czech Republic, July 3-5, 2023, Proceedings, Part I (Lecture Notes in Computer Science, Vol. 14073). Springer, 321-335."},{"key":"e_1_2_1_59_1","volume-title":"Updates and Risks of Third-Party Libraries in Java Projects. In International Conference on Software Maintenance and Evolution. IEEE, 35-45","author":"Wang Ying","year":"2020","unstructured":"Ying Wang, Bihuan Chen, Kaifeng Huang, Bowen Shi, Congying Xu, Xin Peng, Yijian Wu, and Yang Liu. 2020. An Empirical Study of Usages, Updates and Risks of Third-Party Libraries in Java Projects. In International Conference on Software Maintenance and Evolution. IEEE, 35-45."},{"key":"e_1_2_1_60_1","unstructured":"Brett Wooldridge. 2025. SparseBitSet Issue #13. https:\/\/github.com\/brettwooldridge\/SparseBitSet\/issues\/13"},{"key":"e_1_2_1_61_1","volume-title":"International Conference on Software Engineering. ACM, 126:1-126:13","author":"Xia Chunqiu Steven","year":"2024","unstructured":"Chunqiu Steven Xia, Matteo Paltenghi, Jia Le Tian, Michael Pradel, and Lingming Zhang. 2024. Fuzz4All: Universal Fuzzing with Large Language Models. In International Conference on Software Engineering. ACM, 126:1-126:13."},{"key":"e_1_2_1_62_1","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1007\/s10515-023-00380-2","article-title":"qaAskeR + : a novel testing method for question answering software via asking recursive questions","volume":"30","author":"Xie Xiaoyuan","year":"2023","unstructured":"Xiaoyuan Xie, Shuo Jin, and Songqiang Chen. 2023. qaAskeR + : a novel testing method for question answering software via asking recursive questions. Automated Software Engineering 30, 1 (2023), 14.","journal-title":"Automated Software Engineering"},{"key":"e_1_2_1_63_1","volume-title":"Word Closure-Based Metamorphic Testing for Machine Translation. ACM Transactions on Software Engineering and Methodology (jul","author":"Xie Xiaoyuan","year":"2024","unstructured":"Xiaoyuan Xie, Shuo Jin, Songqiang Chen, and Shing-Chi Cheung. 2024. Word Closure-Based Metamorphic Testing for Machine Translation. ACM Transactions on Software Engineering and Methodology (jul 2024)."},{"key":"e_1_2_1_64_1","doi-asserted-by":"publisher","DOI":"10.1145\/3691620.3696020"},{"key":"e_1_2_1_65_1","doi-asserted-by":"publisher","DOI":"10.1145\/3656340"},{"key":"e_1_2_1_66_1","volume-title":"Jia Li, Shuo Liu, Yifan Hong, Xiaoxue Ma, Zhi Jin, and Ge Li.","author":"Yang Zhen","year":"2024","unstructured":"Zhen Yang, Fang Liu, Zhongxing Yu, Jacky Wai Keung, Jia Li, Shuo Liu, Yifan Hong, Xiaoxue Ma, Zhi Jin, and Ge Li. 2024. Exploring and Unleashing the Power of Large Language Models in Automated Code Translation. CoRR abs\/2404.14646 (2024). arXiv:2404.14646"},{"key":"e_1_2_1_67_1","volume-title":"Perception Matters: Detecting Perception Failures of VQA Models Using Metamorphic Testing. In Conference on Computer Vision and Pattern Recognition. Computer Vision Foundation \/ IEEE, 16908-16917","author":"Yuan Yuanyuan","year":"2021","unstructured":"Yuanyuan Yuan, Shuai Wang, Mingyue Jiang, and Tsong Yueh Chen. 2021. Perception Matters: Detecting Perception Failures of VQA Models Using Metamorphic Testing. In Conference on Computer Vision and Pattern Recognition. Computer Vision Foundation \/ IEEE, 16908-16917."},{"key":"e_1_2_1_68_1","doi-asserted-by":"publisher","DOI":"10.1145\/3660783"},{"key":"e_1_2_1_69_1","volume-title":"Automatic Discovery and Cleansing of Numerical Metamorphic Relations. In IEEE International Conference on Software Maintenance and Evolution. IEEE, 235-245","author":"Zhang Bo","year":"2019","unstructured":"Bo Zhang, Hongyu Zhang, Junjie Chen, Dan Hao, and Pablo Moscato. 2019. Automatic Discovery and Cleansing of Numerical Metamorphic Relations. In IEEE International Conference on Software Maintenance and Evolution. IEEE, 235-245."},{"key":"e_1_2_1_70_1","volume-title":"ACM\/IEEE International Conference on Automated Software Engineering. ACM, 701-712","author":"Zhang Jie","year":"2014","unstructured":"Jie Zhang, Junjie Chen, Dan Hao, Yingfei Xiong, Bing Xie, Lu Zhang, and Hong Mei. 2014. Search-based inference of polynomial metamorphic relations. In ACM\/IEEE International Conference on Automated Software Engineering. ACM, 701-712."},{"key":"e_1_2_1_71_1","doi-asserted-by":"publisher","DOI":"10.1109\/SANER64311.2025.00011"},{"key":"e_1_2_1_72_1","doi-asserted-by":"publisher","DOI":"10.1016\/J.INFSOF.2025.107828"},{"key":"e_1_2_1_73_1","doi-asserted-by":"publisher","DOI":"10.1109\/COMPSAC57700.2023.00275"},{"key":"e_1_2_1_74_1","volume-title":"Integrating Artificial Intelligence with Human Expertise: An In-depth Analysis of ChatGPT's Capabilities in Generating Metamorphic Relations. CoRR abs\/2503.22141","author":"Zhang Yifan","year":"2025","unstructured":"Yifan Zhang, Dave Towey, Matthew Pike, Quang-Hung Luu, Huai Liu, and Tsong Yueh Chen. 2025. Integrating Artificial Intelligence with Human Expertise: An In-depth Analysis of ChatGPT's Capabilities in Generating Metamorphic Relations. CoRR abs\/2503.22141 (2025). arXiv:2503.22141 https:\/\/arxiv.org\/abs\/2503.22141"},{"key":"e_1_2_1_75_1","doi-asserted-by":"publisher","DOI":"10.1145\/3728894"},{"key":"e_1_2_1_76_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2018.2876433"},{"key":"e_1_2_1_77_1","unstructured":"Zingg. 2025. Zingg Issue #60. https:\/\/github.com\/zinggAI\/zingg\/issues\/60"}],"container-title":["Proceedings of the ACM on Software Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3808213","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T18:29:40Z","timestamp":1782844180000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3808213"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,30]]},"references-count":77,"journal-issue":{"issue":"FSE","published-print":{"date-parts":[[2026,6,30]]}},"alternative-id":["10.1145\/3808213"],"URL":"https:\/\/doi.org\/10.1145\/3808213","relation":{},"ISSN":["2994-970X"],"issn-type":[{"value":"2994-970X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,30]]}}}