{"title":"可追溯性挑战2013:可追溯性实验的统计分析:肯塔基大学软件验证和验证研究实验室(SVVRL","authors":"Mark Hays, J. Hayes, A. Stromberg, A. Bathke","doi":"10.1109/TEFSE.2013.6620161","DOIUrl":null,"url":null,"abstract":"An important aspect of traceability experiments is the ability to compare techniques. In order to assure proper comparison, it is necessary to perform statistical analysis of the dependent variables collected from technique application. Currently, there is a lack of components in TraceLab to support such analysis. The Software Verification and Validation Research Laboratory (SVVRL) and the Statistics Department of the University of Kentucky have developed a collection of such components as well as a workflow for determining what type of analysis to apply (parametric, non-parametric). The components use industry-accepted R algorithms. The components have been validated using independent standard statistical algorithms applied to publicly available datasets. This work addresses the Purposed grand challenge (research project 4) and Cost-Effective Grand Challenge (research project 4) as well as the Valued Grand Challenge - research project 6.","PeriodicalId":330587,"journal":{"name":"2013 7th International Workshop on Traceability in Emerging Forms of Software Engineering (TEFSE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Traceability Challenge 2013: Statistical analysis for traceability experiments: Software verification and validation research laboratory (SVVRL) of the University of Kentucky\",\"authors\":\"Mark Hays, J. Hayes, A. Stromberg, A. Bathke\",\"doi\":\"10.1109/TEFSE.2013.6620161\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An important aspect of traceability experiments is the ability to compare techniques. In order to assure proper comparison, it is necessary to perform statistical analysis of the dependent variables collected from technique application. Currently, there is a lack of components in TraceLab to support such analysis. The Software Verification and Validation Research Laboratory (SVVRL) and the Statistics Department of the University of Kentucky have developed a collection of such components as well as a workflow for determining what type of analysis to apply (parametric, non-parametric). The components use industry-accepted R algorithms. The components have been validated using independent standard statistical algorithms applied to publicly available datasets. This work addresses the Purposed grand challenge (research project 4) and Cost-Effective Grand Challenge (research project 4) as well as the Valued Grand Challenge - research project 6.\",\"PeriodicalId\":330587,\"journal\":{\"name\":\"2013 7th International Workshop on Traceability in Emerging Forms of Software Engineering (TEFSE)\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-05-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 7th International Workshop on Traceability in Emerging Forms of Software Engineering (TEFSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TEFSE.2013.6620161\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 7th International Workshop on Traceability in Emerging Forms of Software Engineering (TEFSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TEFSE.2013.6620161","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Traceability Challenge 2013: Statistical analysis for traceability experiments: Software verification and validation research laboratory (SVVRL) of the University of Kentucky
An important aspect of traceability experiments is the ability to compare techniques. In order to assure proper comparison, it is necessary to perform statistical analysis of the dependent variables collected from technique application. Currently, there is a lack of components in TraceLab to support such analysis. The Software Verification and Validation Research Laboratory (SVVRL) and the Statistics Department of the University of Kentucky have developed a collection of such components as well as a workflow for determining what type of analysis to apply (parametric, non-parametric). The components use industry-accepted R algorithms. The components have been validated using independent standard statistical algorithms applied to publicly available datasets. This work addresses the Purposed grand challenge (research project 4) and Cost-Effective Grand Challenge (research project 4) as well as the Valued Grand Challenge - research project 6.