{"title":"示例驱动代码审查解释","authors":"Shadikur Rahman, Umme Ayman Koana, Maleknaz Nayebi","doi":"10.1145/3544902.3546639","DOIUrl":null,"url":null,"abstract":"Background: Code reviewing is an essential part of software development to ensure software quality. However, the abundance of review tasks and the intensity of the workload for reviewers negatively impact the quality of the reviews. The short review text is often unactionable. Aims: We propose the Example Driven Review Explanation (EDRE) method to facilitate the code review process by adding additional explanations through examples. EDRE recommends similar code reviews as examples to further explain a review and help a developer to understand the received reviews with less communication overhead. Method: Through an empirical study in an industrial setting and by analyzing 3,722 Code reviews across three open-source projects, we compared five methods of data retrieval, text classification, and text recommendation. Results: EDRE using TF-IDF word embedding along with an SVM classifier can provide practical examples for each code review with 92% F-score and 90% Accuracy. Conclusions: The example-based explanation is an established method for assisting experts in explaining decisions. EDRE can accurately provide a set of context-specific examples to facilitate the code review process in software teams.","PeriodicalId":220679,"journal":{"name":"Proceedings of the 16th ACM / IEEE International Symposium on Empirical Software Engineering and Measurement","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Example Driven Code Review Explanation\",\"authors\":\"Shadikur Rahman, Umme Ayman Koana, Maleknaz Nayebi\",\"doi\":\"10.1145/3544902.3546639\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background: Code reviewing is an essential part of software development to ensure software quality. However, the abundance of review tasks and the intensity of the workload for reviewers negatively impact the quality of the reviews. The short review text is often unactionable. Aims: We propose the Example Driven Review Explanation (EDRE) method to facilitate the code review process by adding additional explanations through examples. EDRE recommends similar code reviews as examples to further explain a review and help a developer to understand the received reviews with less communication overhead. Method: Through an empirical study in an industrial setting and by analyzing 3,722 Code reviews across three open-source projects, we compared five methods of data retrieval, text classification, and text recommendation. Results: EDRE using TF-IDF word embedding along with an SVM classifier can provide practical examples for each code review with 92% F-score and 90% Accuracy. Conclusions: The example-based explanation is an established method for assisting experts in explaining decisions. EDRE can accurately provide a set of context-specific examples to facilitate the code review process in software teams.\",\"PeriodicalId\":220679,\"journal\":{\"name\":\"Proceedings of the 16th ACM / IEEE International Symposium on Empirical Software Engineering and Measurement\",\"volume\":\"72 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 16th ACM / IEEE International Symposium on Empirical Software Engineering and Measurement\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3544902.3546639\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 16th ACM / IEEE International Symposium on Empirical Software Engineering and Measurement","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3544902.3546639","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Background: Code reviewing is an essential part of software development to ensure software quality. However, the abundance of review tasks and the intensity of the workload for reviewers negatively impact the quality of the reviews. The short review text is often unactionable. Aims: We propose the Example Driven Review Explanation (EDRE) method to facilitate the code review process by adding additional explanations through examples. EDRE recommends similar code reviews as examples to further explain a review and help a developer to understand the received reviews with less communication overhead. Method: Through an empirical study in an industrial setting and by analyzing 3,722 Code reviews across three open-source projects, we compared five methods of data retrieval, text classification, and text recommendation. Results: EDRE using TF-IDF word embedding along with an SVM classifier can provide practical examples for each code review with 92% F-score and 90% Accuracy. Conclusions: The example-based explanation is an established method for assisting experts in explaining decisions. EDRE can accurately provide a set of context-specific examples to facilitate the code review process in software teams.