S. S. Kamaruddin, A. Deraman, J. Yahaya, Ruzita Ahmad
{"title":"动态软件质量评估的特征子集选择方法","authors":"S. S. Kamaruddin, A. Deraman, J. Yahaya, Ruzita Ahmad","doi":"10.1109/MYSEC.2011.6140688","DOIUrl":null,"url":null,"abstract":"This article presents a feature subset selection method for the purpose of selecting the appropriate attributes for software quality assessment. The existing software quality assessment models do not support dynamic assessment. In dynamic software quality assessment, new quality attributes can be added to the model as they emerge. Therefore, this work focuses on the development of an intelligent method that is able to learn and adapt new quality attributes into the model to establish dynamic software quality assessment","PeriodicalId":137714,"journal":{"name":"2011 Malaysian Conference in Software Engineering","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Feature subset selection method for dynamic software quality assessment\",\"authors\":\"S. S. Kamaruddin, A. Deraman, J. Yahaya, Ruzita Ahmad\",\"doi\":\"10.1109/MYSEC.2011.6140688\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article presents a feature subset selection method for the purpose of selecting the appropriate attributes for software quality assessment. The existing software quality assessment models do not support dynamic assessment. In dynamic software quality assessment, new quality attributes can be added to the model as they emerge. Therefore, this work focuses on the development of an intelligent method that is able to learn and adapt new quality attributes into the model to establish dynamic software quality assessment\",\"PeriodicalId\":137714,\"journal\":{\"name\":\"2011 Malaysian Conference in Software Engineering\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 Malaysian Conference in Software Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MYSEC.2011.6140688\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Malaysian Conference in Software Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MYSEC.2011.6140688","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Feature subset selection method for dynamic software quality assessment
This article presents a feature subset selection method for the purpose of selecting the appropriate attributes for software quality assessment. The existing software quality assessment models do not support dynamic assessment. In dynamic software quality assessment, new quality attributes can be added to the model as they emerge. Therefore, this work focuses on the development of an intelligent method that is able to learn and adapt new quality attributes into the model to establish dynamic software quality assessment
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