XREPOTEST：面向大型语言模型的多语言仓库级单元测试生成基准评测

Computer Science > Software Engineering arXiv:2608.25939 (cs) [Submitted on 26 Aug 2026 (v1), last revised 15 Sep 2026 (this version, v2)] Title:XREPOTEST: Benchmarking Multilingual Repository-Level Unit Test Generation for Large Language Models Authors:Dung Le Quang, Dong Cao Van, Nam Le Hai, Linh Ngo Van, Anh M. T. Bui, Phuong T. Nguyen View a PDF of the paper titled XREPOTEST: Benchmarking Multilingual Repository-Level Unit Test Generation for Large Language Models, by Dung Le Quang and 5 other authors View PDF HTML (experimental) Abstract:Large language models (LLMs) have shown promise for automated unit test generation, but existing evaluations largely rely on standalone settings and a narrow set of programming languages, overestimating real-world readiness. We introduce XREPOTEST, a multilingual repository-level benchmark for unit test generation spanning five underexplored languages: Rust, Go, Julia, PHP, and Ruby. XREPOTEST evaluates tests under realistic repository constraints using a containerized execution framework and multiple context augmentation strategies, including file-level, LSP-based, and retrieval-based context. Beyond standard metrics such as test pass rate and coverage, we propose Invocation Rate (IR) to assess whether generated tests meaningfully exercise the intended functionality. Experiments with 14 state-of-the-art LLMs, including Claude 4.5, GPT-5.2, DeepSeek V4-Pro, and Qwen families, reveal a substantial gap between standalone and repository-level performance, as well as trade-offs between richer context and test reliability. Overall, XREPOTEST provides a challenging and informative benchmark to advance scalable and robust unit test generation in realistic software environments. The dataset and code are publicly available at: this https URL Comments: Subjects: Software Engineering (cs.SE) Cite as: arXiv:2608.25939 [cs.SE] (or arXiv:2608.25939v2 [cs.SE] for this version) https://doi.org/10.48550/arXiv.2608.25939 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Nam Le Hai [view email] [v1] Wed, 26 Aug 2026 15:53:43 UTC (2,029 KB) [v2] Tue, 15 Sep 2026 15:26:32 UTC (2,033 KB) Full-text links: Access Paper: View a PDF of the paper titled XREPOTEST: Benchmarking Multilingual Repository-Level Unit Test Generation for Large Language Models, by Dung Le Quang and 5 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cs.SE new | recent | 2026-08 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv (What is alphaXiv?) Links to Code Toggle CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub Toggle DagsHub (What is DagsHub?) GotitPub Toggle Gotit.pub (What is GotitPub?) Huggingface Toggle Hugging Face (What is Huggingface?) ScienceCast Toggle ScienceCast (What is ScienceCast?) Demos Demos Replicate Toggle Replicate (What is Replicate?) Spaces Toggle Hugging Face Spaces (What is Spaces?) Spaces Toggle TXYZ.AI (What is TXYZ.AI?) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower (What are Influence Flowers?) Core recommender toggle CORE Recommender (What is CORE?) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)