{"title":"代码评审反馈是如何演变的?:戴尔EMC纵向研究","authors":"R. Wen, Maxime Lamothe, Shane McIntosh","doi":"10.1145/3510457.3513039","DOIUrl":null,"url":null,"abstract":"Code review is an integral part of modern software development, where fellow developers critique the content, premise, and structure of code changes. Organizations like DellEMC have made considerable investment in code reviews, yet tracking the characteristics of feedback that code reviews provide (a primary product of the code reviewing process) is still a difficult process. To understand community and personal feedback trends, we perform a longitudinal study of 39,249 reviews that contain 248,695 review comments from a proprietary project that is developed by DellEMC. To investigate generalizability, we replicate our study on the OpenStackn Ova project. Through an analysis guided by topic models, we observe that more context-specific, technical feedback is introduced as the studied projects and communities age and as the reviewers within those communities accrue experience. This suggests that communities are reaping a larger return on investment in code review as they grow accustomed to the practice and as reviewers hone their skills. The code review trends uncovered by our models present opportunities for enterprises to monitor reviewing tendencies and improve knowledge transfer and reviewer skills.","PeriodicalId":119790,"journal":{"name":"2022 IEEE/ACM 44th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"How Does Code Reviewing Feedback Evolve?: A Longitudinal Study at Dell EMC\",\"authors\":\"R. Wen, Maxime Lamothe, Shane McIntosh\",\"doi\":\"10.1145/3510457.3513039\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Code review is an integral part of modern software development, where fellow developers critique the content, premise, and structure of code changes. Organizations like DellEMC have made considerable investment in code reviews, yet tracking the characteristics of feedback that code reviews provide (a primary product of the code reviewing process) is still a difficult process. To understand community and personal feedback trends, we perform a longitudinal study of 39,249 reviews that contain 248,695 review comments from a proprietary project that is developed by DellEMC. To investigate generalizability, we replicate our study on the OpenStackn Ova project. Through an analysis guided by topic models, we observe that more context-specific, technical feedback is introduced as the studied projects and communities age and as the reviewers within those communities accrue experience. This suggests that communities are reaping a larger return on investment in code review as they grow accustomed to the practice and as reviewers hone their skills. The code review trends uncovered by our models present opportunities for enterprises to monitor reviewing tendencies and improve knowledge transfer and reviewer skills.\",\"PeriodicalId\":119790,\"journal\":{\"name\":\"2022 IEEE/ACM 44th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP)\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE/ACM 44th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3510457.3513039\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE/ACM 44th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3510457.3513039","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
How Does Code Reviewing Feedback Evolve?: A Longitudinal Study at Dell EMC
Code review is an integral part of modern software development, where fellow developers critique the content, premise, and structure of code changes. Organizations like DellEMC have made considerable investment in code reviews, yet tracking the characteristics of feedback that code reviews provide (a primary product of the code reviewing process) is still a difficult process. To understand community and personal feedback trends, we perform a longitudinal study of 39,249 reviews that contain 248,695 review comments from a proprietary project that is developed by DellEMC. To investigate generalizability, we replicate our study on the OpenStackn Ova project. Through an analysis guided by topic models, we observe that more context-specific, technical feedback is introduced as the studied projects and communities age and as the reviewers within those communities accrue experience. This suggests that communities are reaping a larger return on investment in code review as they grow accustomed to the practice and as reviewers hone their skills. The code review trends uncovered by our models present opportunities for enterprises to monitor reviewing tendencies and improve knowledge transfer and reviewer skills.