{"title":"SeSaMe:语义相似的Java方法的数据集","authors":"Marius Kamp, Patrick Kreutzer, M. Philippsen","doi":"10.1109/MSR.2019.00079","DOIUrl":null,"url":null,"abstract":"In the past, techniques for detecting similarly behaving code fragments were often only evaluated with small, artificial oracles or with code originating from programming competitions. Such code fragments differ largely from production codes. To enable more realistic evaluations, this paper presents SeSaMe, a data set of method pairs that are classified according to their semantic similarity. We applied text similarity measures on JavaDoc comments mined from 11 open source repositories and manually classified a selection of 857 pairs.","PeriodicalId":6706,"journal":{"name":"2019 IEEE/ACM 16th International Conference on Mining Software Repositories (MSR)","volume":"110 1","pages":"529-533"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"SeSaMe: A Data Set of Semantically Similar Java Methods\",\"authors\":\"Marius Kamp, Patrick Kreutzer, M. Philippsen\",\"doi\":\"10.1109/MSR.2019.00079\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the past, techniques for detecting similarly behaving code fragments were often only evaluated with small, artificial oracles or with code originating from programming competitions. Such code fragments differ largely from production codes. To enable more realistic evaluations, this paper presents SeSaMe, a data set of method pairs that are classified according to their semantic similarity. We applied text similarity measures on JavaDoc comments mined from 11 open source repositories and manually classified a selection of 857 pairs.\",\"PeriodicalId\":6706,\"journal\":{\"name\":\"2019 IEEE/ACM 16th International Conference on Mining Software Repositories (MSR)\",\"volume\":\"110 1\",\"pages\":\"529-533\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE/ACM 16th International Conference on Mining Software Repositories (MSR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MSR.2019.00079\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE/ACM 16th International Conference on Mining Software Repositories (MSR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MSR.2019.00079","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
SeSaMe: A Data Set of Semantically Similar Java Methods
In the past, techniques for detecting similarly behaving code fragments were often only evaluated with small, artificial oracles or with code originating from programming competitions. Such code fragments differ largely from production codes. To enable more realistic evaluations, this paper presents SeSaMe, a data set of method pairs that are classified according to their semantic similarity. We applied text similarity measures on JavaDoc comments mined from 11 open source repositories and manually classified a selection of 857 pairs.
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