Xing Zhang
2025
Skeleton-Guided-Translation: A Benchmarking Framework for Code Repository Translation with Fine-Grained Quality Evaluation
Xing Zhang
|
Jiaheng Wen
|
Fangkai Yang
|
Yu Kang
|
Pu Zhao
|
Junhao Wang
|
Maoquan Wang
|
Yufan Huang
|
Shengyu Fu
|
Elsie Nallipogu
|
Qingwei Lin
|
Yingnong Dang
|
Saravan Rajmohan
|
Dongmei Zhang
Findings of the Association for Computational Linguistics: EMNLP 2025
Code translation benchmarks are essential for evaluating the accuracy and efficiency of LLM-based systems. Existing benchmarks mainly target individual functions, overlooking repository-level challenges like intermodule coherence and dependency management. Recent repository-level efforts exist, but suffer from poor maintainability and coarse evaluation granularity. We introduce Skeleton-Guided-Translation, a framework for benchmarking Java-to-C# translation at the repository level, featuring fine-grained quality evaluation. It follows a two-step process: first translating repository “skeletons”, then refining the entire repository guided by these skeletons. Based on this, we present TRANSREPO-BENCH , the first test-driven benchmark of high-quality Java repositories paired with C# skeletons, unit tests, and build configurations. Our adaptive unit tests support multiple and incremental translations without manual tuning, enhancing automation and scalability. We also propose fine-grained metrics that evaluate translation quality per test case, overcoming limitations of binary metrics in distinguishing build failures. Evaluations using TRANSREPO-BENCH reveal issues like broken cross-file references, showing that our structured approach reduces dependency errors and preserves interface consistency.
2010
How Well Conditional Random Fields Can be Used in Novel Term Recognition
Xing Zhang
|
Yan Song
|
Alex Chengyu Fang
Proceedings of the 24th Pacific Asia Conference on Language, Information and Computation
Search
Fix author
Co-authors
- Yingnong Dang 1
- Alex Chengyu Fang 1
- Shengyu Fu 1
- Yufan Huang 1
- Yu Kang 1
- show all...