{"title":"Mercem: Method Name Recommendation Based on Call Graph Embedding","authors":"Hiroshi Yonai, Yasuhiro Hayase, H. Kitagawa","doi":"10.1109/APSEC48747.2019.00027","DOIUrl":null,"url":null,"abstract":"Software developers must provide meaningful but short names to identifiers because they strongly affect the comprehensibility of source code. On the other hand, identifier naming can be a difficult and time-consuming task, even for experienced developers. To support identifier naming, several techniques to recommend candidate names have been proposed. These techniques have challenges on the goodness of suggested candidates and limitations of applicable situations. This paper proposes a new approach to recommend method names by applying graph embedding techniques to the call graph. An experiment confirms that the proposed technique can suggest more appropriate name candidates in difficult situations than the state-of-the-art approach.","PeriodicalId":325642,"journal":{"name":"2019 26th Asia-Pacific Software Engineering Conference (APSEC)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 26th Asia-Pacific Software Engineering Conference (APSEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APSEC48747.2019.00027","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13
Abstract
Software developers must provide meaningful but short names to identifiers because they strongly affect the comprehensibility of source code. On the other hand, identifier naming can be a difficult and time-consuming task, even for experienced developers. To support identifier naming, several techniques to recommend candidate names have been proposed. These techniques have challenges on the goodness of suggested candidates and limitations of applicable situations. This paper proposes a new approach to recommend method names by applying graph embedding techniques to the call graph. An experiment confirms that the proposed technique can suggest more appropriate name candidates in difficult situations than the state-of-the-art approach.