{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/multi-swe-bench-a-multilingual-benchmark-for","title":"Multi-SWE-bench: A Multilingual Benchmark for Issue Resolving","arxiv_id":"2504.02605","date":"2025-04-03","proceeding":null,"authors":["Daoguang Zan","Zhirong Huang","Wei Liu","Hanwu Chen","Linhao Zhang","Shulin Xin","Lu Chen","Qi Liu","Xiaojian Zhong","Aoyan Li","Siyao Liu","Yongsheng Xiao","Liangqiang Chen","Yuyu Zhang","Jing Su","Tianyu Liu","Rui Long","Kai Shen","Liang Xiang"],"abstract":"The task of issue resolving is to modify a codebase to generate a patch that addresses a given issue. However, existing benchmarks, such as SWE-bench, focus almost exclusively on Python, making them insufficient for evaluating Large Language Models (LLMs) across diverse software ecosystems. To address this, we introduce a multilingual issue-resolving benchmark, called Multi-SWE-bench, covering Java, TypeScript, JavaScript, Go, Rust, C, and C++. It includes a total of 1,632 high-quality instances, which were carefully annotated from 2,456 candidates by 68 expert annotators, ensuring that the benchmark can provide an accurate and reliable evaluation. Based on Multi-SWE-bench, we evaluate a series of state-of-the-art models using three representative methods (Agentless, SWE-agent, and OpenHands) and present a comprehensive analysis with key empirical insights. In addition, we launch a Multi-SWE-RL open-source community, aimed at building large-scale reinforcement learning (RL) training datasets for issue-resolving tasks. As an initial contribution, we release a set of 4,723 well-structured instances spanning seven programming languages, laying a solid foundation for RL research in this domain. More importantly, we open-source our entire data production pipeline, along with detailed tutorials, encouraging the open-source community to continuously contribute and expand the dataset. We envision our Multi-SWE-bench and the ever-growing Multi-SWE-RL community as catalysts for advancing RL toward its full potential, bringing us one step closer to the dawn of AGI.","url_abs":"https://arxiv.org/abs/2504.02605v1","url_pdf":"https://arxiv.org/pdf/2504.02605v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"multi-swe-bench-a-multilingual-benchmark-for","repo_url":"https://github.com/multi-swe-bench/experiments","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"Apache-2.0"}},{"paper_slug":"multi-swe-bench-a-multilingual-benchmark-for","repo_url":"https://github.com/multi-swe-bench/mopenhands","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"multi-swe-bench-a-multilingual-benchmark-for","repo_url":"https://github.com/multi-swe-bench/multi-swe-bench","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"reinforcement-learning-1","task_name":"Reinforcement Learning (RL)"}],"methods":[{"method_slug":"focus","method_name":"Focus"},{"method_slug":"set","method_name":"SET"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2504.02605","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2504.02605"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/multi-swe-bench/experiments","reach":{"status":"ok","spdx":"Apache-2.0"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/multi-swe-bench/mopenhands","reach":{"status":"ok","spdx":"MIT"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/multi-swe-bench/multi-swe-bench","reach":null}],"summary":{"ran_honours":1,"unverified":3},"by_repo_kind":{"official":{"samples":4,"ran":1,"repositories":2}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"443c0434fc392250","entry":"get_failed_number","repo":"multi-swe-bench/multi-swe-bench","repo_kind":"official","path":"multi_swe_bench/collect/build_dataset.py","file_url":"https://github.com/multi-swe-bench/multi-swe-bench/blob/HEAD/multi_swe_bench/collect/build_dataset.py","link_basis":"first_harvest_node","language":"python","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"well_formed","behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"443c0434fc392250"}},{"code_sha256_prefix":"ef2ef516c292f4b3","entry":"get_console_handler","repo":"multi-swe-bench/mopenhands","repo_kind":"official","path":"openhands/core/logger.py","file_url":"https://github.com/multi-swe-bench/mopenhands/blob/HEAD/openhands/core/logger.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"ef2ef516c292f4b3"}},{"code_sha256_prefix":"c67038544ccacc52","entry":"get_file_handler","repo":"multi-swe-bench/mopenhands","repo_kind":"official","path":"openhands/core/logger.py","file_url":"https://github.com/multi-swe-bench/mopenhands/blob/HEAD/openhands/core/logger.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"c67038544ccacc52"}},{"code_sha256_prefix":"09b60907c4eb026a","entry":"strip_ansi","repo":"multi-swe-bench/mopenhands","repo_kind":"official","path":"openhands/core/logger.py","file_url":"https://github.com/multi-swe-bench/mopenhands/blob/HEAD/openhands/core/logger.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"09b60907c4eb026a"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}