STACC：使用SentenceTransformers的代码注释分类
STACC: Code Comment Classification using SentenceTransformers
摘要：
代码注释是关于软件工件信息的关键资源。根据用例的不同，只有某些类型的注释是有用的。因此，已经提出了对这些评论进行分类的自动方法。在这项工作中，我们提出，STACC，一组基于SentenceTransformers的二进制分类器，以满足这一需求。这些轻量级分类器在NLBSE Code Comment Classification工具竞赛数据集上进行了训练和测试，并以显著的优势超过了基线，实现了0.31的平均F1得分为0.74，提高了139%。复制包以及模型本身都是公开的。
英文摘要：
Code comments are a key resource for information about software artefacts. Depending on the use case, only some types of comments are useful. Thus, automatic approaches to classify these comments have been proposed. In this work, we address this need by proposing, STACC, a set of SentenceTransformers-based binary classifiers. These lightweight classifiers are trained and tested on the NLBSE Code Comment Classification tool competition dataset, and surpass the baseline by a significant margin, achieving an average F1 score of 0.74 against the baseline of 0.31, which is an improvement of 139%. A replication package, as well as the models themselves, are publicly available.
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。
