Thai-Bao Do, Huu-Nghia H. Nguyen, Bao-Linh L. Mai, Vu Nguyen
{"title":"挖掘和创建软件存储库数据集","authors":"Thai-Bao Do, Huu-Nghia H. Nguyen, Bao-Linh L. Mai, Vu Nguyen","doi":"10.1109/NICS51282.2020.9335894","DOIUrl":null,"url":null,"abstract":"Mining software repositories to extract meaningful information from them has become an important topic in software engineering. This paper presents our study to mine a very large dataset consisting of over three million software repositories across many version control systems and create derived data for future studies. Through this study, we propose a method for detecting forks and duplicates in repositories. We also preliminarily investigate the possible correlations between forking patterns, software health and risks, and success indicators.","PeriodicalId":308944,"journal":{"name":"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mining and Creating a Software Repositories Dataset\",\"authors\":\"Thai-Bao Do, Huu-Nghia H. Nguyen, Bao-Linh L. Mai, Vu Nguyen\",\"doi\":\"10.1109/NICS51282.2020.9335894\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mining software repositories to extract meaningful information from them has become an important topic in software engineering. This paper presents our study to mine a very large dataset consisting of over three million software repositories across many version control systems and create derived data for future studies. Through this study, we propose a method for detecting forks and duplicates in repositories. We also preliminarily investigate the possible correlations between forking patterns, software health and risks, and success indicators.\",\"PeriodicalId\":308944,\"journal\":{\"name\":\"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NICS51282.2020.9335894\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NICS51282.2020.9335894","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mining and Creating a Software Repositories Dataset
Mining software repositories to extract meaningful information from them has become an important topic in software engineering. This paper presents our study to mine a very large dataset consisting of over three million software repositories across many version control systems and create derived data for future studies. Through this study, we propose a method for detecting forks and duplicates in repositories. We also preliminarily investigate the possible correlations between forking patterns, software health and risks, and success indicators.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
