GIRT-Model：问题报告模板的自动生成
GIRT-Model: Automated Generation of Issue Report Templates
AI总结：
GIRT-Model是一个基于指令微调T5-base的辅助语言模型，能根据开发者指令自动生成问题报告模板，在ROUGE、BLEU、METEOR和人工评估中优于通用模型，并获用户认可。
摘要：
GitHub和GitLab等平台引入了问题报告模板（IRT），以实现更有效的问题管理和更好地符合开发者的期望。然而，这些模板在大多数代码库中并未被广泛采用，目前也没有工具可帮助开发者生成这些模板。在本工作中，我们介绍了GIRT-Model，一个辅助语言模型，可根据开发者关于结构和必要字段的指令自动生成IRT。我们创建了GIRT-Instruct，一个包含指令和IRT配对的数据集，其中IRT来源于GitHub代码库。我们使用GIRT-Instruct对T5-base模型进行指令微调，以创建GIRT-Model。在我们的实验中，GIRT-Model在IRT生成方面优于通用语言模型（不同参数规模的T5和Flan-T5），在ROUGE、BLEU、METEOR和人工评估中取得了显著更高的分数。此外，我们在一项用户研究中分析了GIRT-Model的有效性，参与者使用GIRT-Model编写了简短的IRT。我们的结果表明，参与者认为GIRT-Model在模板自动生成中很有用。我们希望，通过使用GIRT-Model，能够鼓励更多开发者在他们的代码库中采用IRT。我们公开发布了代码、数据集和模型，网址为https://github.com/ISE-Research/girt-model。
英文摘要：
Platforms such as GitHub and GitLab introduce Issue Report Templates (IRTs) to enable more effective issue management and better alignment with developer expectations. However, these templates are not widely adopted in most repositories, and there is currently no tool available to aid developers in generating them. In this work, we introduce GIRT-Model, an assistant language model that automatically generates IRTs based on the developer's instructions regarding the structure and necessary fields. We create GIRT-Instruct, a dataset comprising pairs of instructions and IRTs, with the IRTs sourced from GitHub repositories. We use GIRT-Instruct to instruction-tune a T5-base model to create the GIRT-Model. In our experiments, GIRT-Model outperforms general language models (T5 and Flan-T5 with different parameter sizes) in IRT generation by achieving significantly higher scores in ROUGE, BLEU, METEOR, and human evaluation. Additionally, we analyze the effectiveness of GIRT-Model in a user study in which participants wrote short IRTs with GIRT-Model. Our results show that the participants find GIRT-Model useful in the automated generation of templates. We hope that through the use of GIRT-Model, we can encourage more developers to adopt IRTs in their repositories. We publicly release our code, dataset, and model at https://github.com/ISE-Research/girt-model.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
