{"title":"Recovering traceability links between a simple natural language sentence and source code using domain ontologies","authors":"Takashi Yoshikawa, Shinpei Hayashi, M. Saeki","doi":"10.1109/ICSM.2009.5306390","DOIUrl":null,"url":null,"abstract":"This paper proposes an ontology-based technique for recovering traceability links between a natural language sentence specifying features of a software product and the source code of the product. Some software products have been released without detailed documentation. To automatically detect code fragments associated with the functional descriptions written in the form of simple sentences, the relationships between source code structures and problem domains are important. In our approach, we model the knowledge of the problem domains as domain ontologies. By using semantic relationships of the ontologies in addition to method invocation relationships and the similarity between an identifier on the code and words in the sentences, we can detect code fragments corresponding to the sentences. A case study within a domain of painting software shows that we obtained results of higher quality than without ontologies.","PeriodicalId":247441,"journal":{"name":"2009 IEEE International Conference on Software Maintenance","volume":"82 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Conference on Software Maintenance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSM.2009.5306390","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
This paper proposes an ontology-based technique for recovering traceability links between a natural language sentence specifying features of a software product and the source code of the product. Some software products have been released without detailed documentation. To automatically detect code fragments associated with the functional descriptions written in the form of simple sentences, the relationships between source code structures and problem domains are important. In our approach, we model the knowledge of the problem domains as domain ontologies. By using semantic relationships of the ontologies in addition to method invocation relationships and the similarity between an identifier on the code and words in the sentences, we can detect code fragments corresponding to the sentences. A case study within a domain of painting software shows that we obtained results of higher quality than without ontologies.