@inproceedings{kuhar-etal-2025-libevolutioneval,
    title = "{L}ib{E}volution{E}val: A Benchmark and Study for Version-Specific Code Generation",
    author = "Kuhar, Sachit  and
      Ahmad, Wasi Uddin  and
      Wang, Zijian  and
      Jain, Nihal  and
      Qian, Haifeng  and
      Ray, Baishakhi  and
      Ramanathan, Murali Krishna  and
      Ma, Xiaofei  and
      Deoras, Anoop",
    editor = "Chiruzzo, Luis  and
      Ritter, Alan  and
      Wang, Lu",
    booktitle = "Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)",
    month = apr,
    year = "2025",
    address = "Albuquerque, New Mexico",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/Author-Pages-WenzhengZhang-ZhengyanShi-ShuYang/2025.naacl-long.348/",
    doi = "10.18653/v1/2025.naacl-long.348",
    pages = "6826--6840",
    ISBN = "979-8-89176-189-6",
    abstract = "Recent advancements in code completion models have primarily focused on local file contexts. However, these studies do not fully capture the complexity of real-world software development, which often requires the use of rapidly-evolving public libraries. To address this gap, we introduce LibEvolutionEval, a comprehensive study that emphasizes the need to understand library evolution to perform accurate in-line code completions. LibEvolutionEvaloffers a version-specific code-completion task across eight libraries as they evolve over the years, along with an in-depth analysis of the evolution of two widely used and well-maintained public libraries: PyTorch and Matplotlib. We evaluate several popular models and find that public library evolution significantly affects their performance. To mitigate this, we explored how retrieving version-specific library documentation and prompt-based techniques can enhance model capability in dealing with these fast-evolving packages. This suggests a promising path forward for better handling fast-evolving libraries. Our tasks will be made publicly available upon acceptance."
}