Skeleton-Guided-Translation: A Benchmarking Framework for Code Repository Translation with Fine-Grained Quality Evaluation
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| Format: | Preprint |
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2025
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| author | Zhang, Xing Wen, Jiaheng Yang, Fangkai Zhao, Pu Kang, Yu Wang, Junhao Wang, Maoquan Huang, Yufan Nallipogu, Elsie Lin, Qingwei Dang, Yingnong Rajmohan, Saravan Zhang, Dongmei Zhang, Qi |
| author_facet | Zhang, Xing Wen, Jiaheng Yang, Fangkai Zhao, Pu Kang, Yu Wang, Junhao Wang, Maoquan Huang, Yufan Nallipogu, Elsie Lin, Qingwei Dang, Yingnong Rajmohan, Saravan Zhang, Dongmei Zhang, Qi |
| contents | The advancement of large language models has intensified the need to modernize enterprise applications and migrate legacy systems to secure, versatile languages. However, existing code translation benchmarks primarily focus on individual functions, overlooking the complexities involved in translating entire repositories, such as maintaining inter-module coherence and managing dependencies. While some recent repository-level translation benchmarks attempt to address these challenges, they still face limitations, including poor maintainability and overly coarse evaluation granularity, which make them less developer-friendly. We introduce Skeleton-Guided-Translation, a framework for repository-level Java to C# code translation with fine-grained quality evaluation. It uses a two-step process: first translating the repository's structural "skeletons", then translating the full repository guided by these skeletons. Building on this, we present TRANSREPO-BENCH, a benchmark of high quality open-source Java repositories and their corresponding C# skeletons, including matching unit tests and build configurations. Our unit tests are fixed and can be applied across multiple or incremental translations without manual adjustments, enhancing automation and scalability in evaluations. Additionally, we develop fine-grained evaluation metrics that assess translation quality at the individual test case level, addressing traditional binary metrics' inability to distinguish when build failures cause all tests to fail. Evaluations using TRANSREPO-BENCH highlight key challenges and advance more accurate repository level code translation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_16050 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Skeleton-Guided-Translation: A Benchmarking Framework for Code Repository Translation with Fine-Grained Quality Evaluation Zhang, Xing Wen, Jiaheng Yang, Fangkai Zhao, Pu Kang, Yu Wang, Junhao Wang, Maoquan Huang, Yufan Nallipogu, Elsie Lin, Qingwei Dang, Yingnong Rajmohan, Saravan Zhang, Dongmei Zhang, Qi Software Engineering Artificial Intelligence The advancement of large language models has intensified the need to modernize enterprise applications and migrate legacy systems to secure, versatile languages. However, existing code translation benchmarks primarily focus on individual functions, overlooking the complexities involved in translating entire repositories, such as maintaining inter-module coherence and managing dependencies. While some recent repository-level translation benchmarks attempt to address these challenges, they still face limitations, including poor maintainability and overly coarse evaluation granularity, which make them less developer-friendly. We introduce Skeleton-Guided-Translation, a framework for repository-level Java to C# code translation with fine-grained quality evaluation. It uses a two-step process: first translating the repository's structural "skeletons", then translating the full repository guided by these skeletons. Building on this, we present TRANSREPO-BENCH, a benchmark of high quality open-source Java repositories and their corresponding C# skeletons, including matching unit tests and build configurations. Our unit tests are fixed and can be applied across multiple or incremental translations without manual adjustments, enhancing automation and scalability in evaluations. Additionally, we develop fine-grained evaluation metrics that assess translation quality at the individual test case level, addressing traditional binary metrics' inability to distinguish when build failures cause all tests to fail. Evaluations using TRANSREPO-BENCH highlight key challenges and advance more accurate repository level code translation. |
| title | Skeleton-Guided-Translation: A Benchmarking Framework for Code Repository Translation with Fine-Grained Quality Evaluation |
| topic | Software Engineering Artificial Intelligence |
| url | https://arxiv.org/abs/2501.16050 |