JCST_Replication

Please cite this dataset as:Huang ZJ, Shao ZQ, Fan GS et al. Community smell occurrence prediction on multi-granularity by developer-oriented features and process metrics. JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY 37(1): 1–25 Jan. 2022. DOI 10.1007/s11390-021-1596-11. data.csv contains features and prediction classes applied to train our machine learners. Each row represents features of one developer.2. The .conf files are configurations to perform Codeface4Smells detections. The manual and source code of the tool is available in: https://github.com/maelstromdat/CodeFace4Smells3. The sentiment dataset is available in: http://ansymore.uantwerpen.be/system/files/uploads/artefacts/alessandro/MSR16/archive3.zip请按以下方式引用本数据集：黄志杰、邵子强、范国生等. 基于开发者导向特征与过程度量的多粒度社区代码异味发生预测. 《计算机科学技术学报》, 2022年1月, 37(1): 1–25. DOI: 10.1007/s11390-021-1596-11. 1. data.csv 文件包含用于训练机器学习模型的特征与预测类别，每一行对应一名开发者的特征数据。 2. .conf 格式文件为执行 Codeface4Smells 检测的配置文件，该工具的使用手册与源代码可从以下链接获取：https://github.com/maelstromdat/CodeFace4Smells 3. 情感数据集可从以下链接获取：http://ansymore.uantwerpen.be/system/files/uploads/artefacts/alessandro/MSR16/archive3.zip