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chore(seo): add google search console verification
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‎site/404.html‎

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<!-- Google Scholar Meta Tags -->
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<meta name="citation_title" content="Advances, Frontiers, and Future of Issue Resolution in Software Engineering: A Comprehensive Survey">
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<!-- Authors -->
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<meta name="citation_author" content="Li, Caihua">
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<meta name="citation_author" content="Guo, Lianghong">
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<meta name="citation_author" content="Wang, Yanlin">
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<meta name="citation_author" content="Tao, Wei">
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<meta name="citation_author" content="Shan, Zhenyu">
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<meta name="citation_author" content="Liu, Mingwei">
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<meta name="citation_author" content="Chen, Jiachi">
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<meta name="citation_author" content="Song, Haoyu">
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<meta name="citation_author" content="Tang, Duyu">
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<meta name="citation_author" content="Zhang, Hongyu">
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<meta name="citation_author" content="Zheng, Zibin">
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<!-- Publication Date (使用当前日期，论文发布后需更新) -->
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<meta name="citation_publication_date" content="2025/01/04">
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<!-- PDF URL (需要在论文正式发布后更新) -->
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<meta name="citation_pdf_url" content="https://github.com/DeepSoftwareAnalytics/Awesome-Issue-Resolution/blob/main/docs/Advances%2C%20Frontiers%2C%20and%20Future%20of%20Issue%20Resolution%20in%20Software%20Engineering%20A%20Comprehensive%20Survey.pdf">
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<!-- 🔄 TODO: 发布到 arXiv 后，取消下面这行的注释并填写正确的 arXiv ID -->
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<!-- <meta name="citation_arxiv_id" content="2501.xxxxx"> -->
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<!-- 🔄 TODO: 发布到 arXiv 后，取消下面这行的注释 -->
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<!-- <meta name="citation_journal_title" content="arXiv preprint arXiv:2501.xxxxx"> -->
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<!-- 🔄 TODO: 如果被会议接收，取消下面这行的注释并填写会议名称 -->
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<!-- <meta name="citation_conference_title" content="Proceedings of ICSE 2026"> -->
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<!-- Abstract -->
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<meta name="citation_abstract" content="Issue resolution, a complex Software Engineering (SWE) task integral to real-world development, has emerged as a compelling challenge for artificial intelligence. The establishment of benchmarks like SWE-bench revealed this task as profoundly difficult for large language models, thereby significantly accelerating the evolution of autonomous coding agents. This paper presents a systematic survey of this emerging domain. We begin by examining data construction pipelines, covering automated collection and synthesis approaches. We then provide a comprehensive analysis of methodologies, spanning training-free frameworks with their modular components to training-based techniques, including supervised fine-tuning and reinforcement learning. Subsequently, we discuss critical analyses of data quality and agent behavior, alongside practical applications. Finally, we identify key challenges and outline promising directions for future research. An open-source repository is maintained at https://github.com/DeepSoftwareAnalytics/Awesome-Issue-Resolution to serve as a dynamic resource in this field.">
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<!-- Keywords -->
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<meta name="citation_keywords" content="Software Engineering; Issue Resolution; Large Language Models; LLMs; GitHub; Automated Program Repair; Code Generation; SWE-bench">
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<!-- Open Graph Meta Tags for social sharing -->
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<meta property="og:title" content="Awesome Issue Resolution - A Comprehensive Survey">
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<meta property="og:description" content="A systematic survey on LLM-based Issue Resolution in Software Engineering">
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<meta property="og:url" content="https://deepsoftwareanalytics.github.io/Awesome-Issue-Resolution/">
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<meta property="og:type" content="article">
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<meta property="og:image" content="https://deepsoftwareanalytics.github.io/Awesome-Issue-Resolution/images/awesome-issue-resolution.png">
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<meta name="twitter:card" content="summary_large_image">
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<meta name="twitter:title" content="Awesome Issue Resolution - A Comprehensive Survey">
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<meta name="twitter:description" content="A systematic survey on LLM-based Issue Resolution in Software Engineering">
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<meta name="twitter:image" content="https://deepsoftwareanalytics.github.io/Awesome-Issue-Resolution/images/awesome-issue-resolution.png">
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‎site/about/index.html‎

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<meta name="citation_title" content="Advances, Frontiers, and Future of Issue Resolution in Software Engineering: A Comprehensive Survey">
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<!-- Authors -->
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<meta name="citation_author" content="Li, Caihua">
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<meta name="citation_author" content="Guo, Lianghong">
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<meta name="citation_author" content="Wang, Yanlin">
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<meta name="citation_author" content="Tao, Wei">
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<meta name="citation_author" content="Shan, Zhenyu">
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<meta name="citation_author" content="Liu, Mingwei">
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<meta name="citation_author" content="Chen, Jiachi">
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<meta name="citation_author" content="Song, Haoyu">
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<meta name="citation_author" content="Tang, Duyu">
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<meta name="citation_author" content="Zhang, Hongyu">
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<meta name="citation_author" content="Zheng, Zibin">
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<!-- Publication Date (使用当前日期，论文发布后需更新) -->
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<meta name="citation_publication_date" content="2025/01/04">
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<!-- PDF URL (需要在论文正式发布后更新) -->
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<meta name="citation_pdf_url" content="https://github.com/DeepSoftwareAnalytics/Awesome-Issue-Resolution/blob/main/docs/Advances%2C%20Frontiers%2C%20and%20Future%20of%20Issue%20Resolution%20in%20Software%20Engineering%20A%20Comprehensive%20Survey.pdf">
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<!-- 🔄 TODO: 发布到 arXiv 后，取消下面这行的注释并填写正确的 arXiv ID -->
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<!-- <meta name="citation_conference_title" content="Proceedings of ICSE 2026"> -->
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<!-- Abstract -->
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<meta name="citation_abstract" content="Issue resolution, a complex Software Engineering (SWE) task integral to real-world development, has emerged as a compelling challenge for artificial intelligence. The establishment of benchmarks like SWE-bench revealed this task as profoundly difficult for large language models, thereby significantly accelerating the evolution of autonomous coding agents. This paper presents a systematic survey of this emerging domain. We begin by examining data construction pipelines, covering automated collection and synthesis approaches. We then provide a comprehensive analysis of methodologies, spanning training-free frameworks with their modular components to training-based techniques, including supervised fine-tuning and reinforcement learning. Subsequently, we discuss critical analyses of data quality and agent behavior, alongside practical applications. Finally, we identify key challenges and outline promising directions for future research. An open-source repository is maintained at https://github.com/DeepSoftwareAnalytics/Awesome-Issue-Resolution to serve as a dynamic resource in this field.">
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<!-- Keywords -->
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<meta name="citation_keywords" content="Software Engineering; Issue Resolution; Large Language Models; LLMs; GitHub; Automated Program Repair; Code Generation; SWE-bench">
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<!-- Open Graph Meta Tags for social sharing -->
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<meta property="og:title" content="Awesome Issue Resolution - A Comprehensive Survey">
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<meta property="og:description" content="A systematic survey on LLM-based Issue Resolution in Software Engineering">
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<meta property="og:url" content="https://deepsoftwareanalytics.github.io/Awesome-Issue-Resolution/">
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<meta property="og:type" content="article">
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<meta property="og:image" content="https://deepsoftwareanalytics.github.io/Awesome-Issue-Resolution/images/awesome-issue-resolution.png">
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<meta name="twitter:card" content="summary_large_image">
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<meta name="twitter:title" content="Awesome Issue Resolution - A Comprehensive Survey">
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<meta name="twitter:description" content="A systematic survey on LLM-based Issue Resolution in Software Engineering">
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<meta name="twitter:image" content="https://deepsoftwareanalytics.github.io/Awesome-Issue-Resolution/images/awesome-issue-resolution.png">
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‎site/analysis/index.html‎

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<meta name="citation_title" content="Advances, Frontiers, and Future of Issue Resolution in Software Engineering: A Comprehensive Survey">
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<!-- Authors -->
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<meta name="citation_author" content="Li, Caihua">
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<meta name="citation_author" content="Guo, Lianghong">
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<meta name="citation_author" content="Wang, Yanlin">
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<meta name="citation_author" content="Tao, Wei">
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<meta name="citation_author" content="Shan, Zhenyu">
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<meta name="citation_author" content="Liu, Mingwei">
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<meta name="citation_author" content="Chen, Jiachi">
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<meta name="citation_author" content="Song, Haoyu">
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<meta name="citation_author" content="Tang, Duyu">
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<meta name="citation_author" content="Zhang, Hongyu">
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<meta name="citation_author" content="Zheng, Zibin">
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<!-- Publication Date (使用当前日期，论文发布后需更新) -->
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<meta name="citation_publication_date" content="2025/01/04">
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<!-- PDF URL (需要在论文正式发布后更新) -->
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<meta name="citation_pdf_url" content="https://github.com/DeepSoftwareAnalytics/Awesome-Issue-Resolution/blob/main/docs/Advances%2C%20Frontiers%2C%20and%20Future%20of%20Issue%20Resolution%20in%20Software%20Engineering%20A%20Comprehensive%20Survey.pdf">
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<!-- 🔄 TODO: 发布到 arXiv 后，取消下面这行的注释并填写正确的 arXiv ID -->
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<!-- 🔄 TODO: 如果被会议接收，取消下面这行的注释并填写会议名称 -->
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<!-- <meta name="citation_conference_title" content="Proceedings of ICSE 2026"> -->
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<!-- Abstract -->
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<meta name="citation_abstract" content="Issue resolution, a complex Software Engineering (SWE) task integral to real-world development, has emerged as a compelling challenge for artificial intelligence. The establishment of benchmarks like SWE-bench revealed this task as profoundly difficult for large language models, thereby significantly accelerating the evolution of autonomous coding agents. This paper presents a systematic survey of this emerging domain. We begin by examining data construction pipelines, covering automated collection and synthesis approaches. We then provide a comprehensive analysis of methodologies, spanning training-free frameworks with their modular components to training-based techniques, including supervised fine-tuning and reinforcement learning. Subsequently, we discuss critical analyses of data quality and agent behavior, alongside practical applications. Finally, we identify key challenges and outline promising directions for future research. An open-source repository is maintained at https://github.com/DeepSoftwareAnalytics/Awesome-Issue-Resolution to serve as a dynamic resource in this field.">
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<!-- Keywords -->
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<meta name="citation_keywords" content="Software Engineering; Issue Resolution; Large Language Models; LLMs; GitHub; Automated Program Repair; Code Generation; SWE-bench">
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<!-- Open Graph Meta Tags for social sharing -->
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<meta property="og:title" content="Awesome Issue Resolution - A Comprehensive Survey">
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<meta property="og:description" content="A systematic survey on LLM-based Issue Resolution in Software Engineering">
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<meta property="og:url" content="https://deepsoftwareanalytics.github.io/Awesome-Issue-Resolution/">
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<meta property="og:type" content="article">
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<meta property="og:image" content="https://deepsoftwareanalytics.github.io/Awesome-Issue-Resolution/images/awesome-issue-resolution.png">
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<!-- Twitter Card Meta Tags -->
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<meta name="twitter:card" content="summary_large_image">
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<meta name="twitter:title" content="Awesome Issue Resolution - A Comprehensive Survey">
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<meta name="twitter:description" content="A systematic survey on LLM-based Issue Resolution in Software Engineering">
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<meta name="twitter:image" content="https://deepsoftwareanalytics.github.io/Awesome-Issue-Resolution/images/awesome-issue-resolution.png">
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‎site/cite/index.html‎

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<!-- Google Scholar Meta Tags -->
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<meta name="citation_title" content="Advances, Frontiers, and Future of Issue Resolution in Software Engineering: A Comprehensive Survey">
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<!-- Authors -->
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<meta name="citation_author" content="Li, Caihua">
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<meta name="citation_author" content="Guo, Lianghong">
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<meta name="citation_author" content="Wang, Yanlin">
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<meta name="citation_author" content="Tao, Wei">
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<meta name="citation_author" content="Shan, Zhenyu">
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<meta name="citation_author" content="Liu, Mingwei">
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<meta name="citation_author" content="Chen, Jiachi">
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<meta name="citation_author" content="Song, Haoyu">
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<meta name="citation_author" content="Tang, Duyu">
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<meta name="citation_author" content="Zhang, Hongyu">
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<meta name="citation_author" content="Zheng, Zibin">
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<!-- Publication Date (使用当前日期，论文发布后需更新) -->
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<meta name="citation_publication_date" content="2025/01/04">
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<!-- PDF URL (需要在论文正式发布后更新) -->
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<meta name="citation_pdf_url" content="https://github.com/DeepSoftwareAnalytics/Awesome-Issue-Resolution/blob/main/docs/Advances%2C%20Frontiers%2C%20and%20Future%20of%20Issue%20Resolution%20in%20Software%20Engineering%20A%20Comprehensive%20Survey.pdf">
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<!-- 🔄 TODO: 发布到 arXiv 后，取消下面这行的注释并填写正确的 arXiv ID -->
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<!-- <meta name="citation_conference_title" content="Proceedings of ICSE 2026"> -->
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<!-- Abstract -->
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<meta name="citation_abstract" content="Issue resolution, a complex Software Engineering (SWE) task integral to real-world development, has emerged as a compelling challenge for artificial intelligence. The establishment of benchmarks like SWE-bench revealed this task as profoundly difficult for large language models, thereby significantly accelerating the evolution of autonomous coding agents. This paper presents a systematic survey of this emerging domain. We begin by examining data construction pipelines, covering automated collection and synthesis approaches. We then provide a comprehensive analysis of methodologies, spanning training-free frameworks with their modular components to training-based techniques, including supervised fine-tuning and reinforcement learning. Subsequently, we discuss critical analyses of data quality and agent behavior, alongside practical applications. Finally, we identify key challenges and outline promising directions for future research. An open-source repository is maintained at https://github.com/DeepSoftwareAnalytics/Awesome-Issue-Resolution to serve as a dynamic resource in this field.">
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<!-- Keywords -->
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<meta name="citation_keywords" content="Software Engineering; Issue Resolution; Large Language Models; LLMs; GitHub; Automated Program Repair; Code Generation; SWE-bench">
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<!-- Open Graph Meta Tags for social sharing -->
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<meta property="og:title" content="Awesome Issue Resolution - A Comprehensive Survey">
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<meta property="og:description" content="A systematic survey on LLM-based Issue Resolution in Software Engineering">
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<meta property="og:url" content="https://deepsoftwareanalytics.github.io/Awesome-Issue-Resolution/">
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<meta property="og:type" content="article">
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<meta property="og:image" content="https://deepsoftwareanalytics.github.io/Awesome-Issue-Resolution/images/awesome-issue-resolution.png">
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<meta name="twitter:card" content="summary_large_image">
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<meta name="twitter:title" content="Awesome Issue Resolution - A Comprehensive Survey">
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<meta name="twitter:description" content="A systematic survey on LLM-based Issue Resolution in Software Engineering">
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