S. Biffl, Marcos Kalinowski, F. Ekaputra, Amadeu Anderlin Neto, T. Conte, D. Winkler
{"title":"对受控实验中有效性威胁和控制行为的语义知识库的研究","authors":"S. Biffl, Marcos Kalinowski, F. Ekaputra, Amadeu Anderlin Neto, T. Conte, D. Winkler","doi":"10.1145/2652524.2652568","DOIUrl":null,"url":null,"abstract":"[Context] Experiment planners need to be aware of relevant Threats to Validity (TTVs), so they can devise effective control actions or accept the risk. [Objective] The aim of this paper is to introduce a TTV knowledge base (KB) that supports experiment planners in identifying relevant TTVs in their research context and actions to control these TTVs. [Method] We identified requirements, designed and populated a TTV KB with data extracted during a systematic review: 63 TTVs and 149 control actions from 206 peer-reviewed published software engineering experiments. We conducted an initial proof of concept on the feasibility of using the TTV KB and analyzed its content. [Results] The proof of concept and content analysis provided indications that experiment planners can benefit from an extensible TTV KB for identifying relevant TTVs and control actions in their specific context. [Conclusions] The TTV KB should be further evaluated and evolved in a variety of software engineering contexts.","PeriodicalId":124452,"journal":{"name":"International Symposium on Empirical Software Engineering and Measurement","volume":"254 3","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Towards a semantic knowledge base on threats to validity and control actions in controlled experiments\",\"authors\":\"S. Biffl, Marcos Kalinowski, F. Ekaputra, Amadeu Anderlin Neto, T. Conte, D. Winkler\",\"doi\":\"10.1145/2652524.2652568\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"[Context] Experiment planners need to be aware of relevant Threats to Validity (TTVs), so they can devise effective control actions or accept the risk. [Objective] The aim of this paper is to introduce a TTV knowledge base (KB) that supports experiment planners in identifying relevant TTVs in their research context and actions to control these TTVs. [Method] We identified requirements, designed and populated a TTV KB with data extracted during a systematic review: 63 TTVs and 149 control actions from 206 peer-reviewed published software engineering experiments. We conducted an initial proof of concept on the feasibility of using the TTV KB and analyzed its content. [Results] The proof of concept and content analysis provided indications that experiment planners can benefit from an extensible TTV KB for identifying relevant TTVs and control actions in their specific context. [Conclusions] The TTV KB should be further evaluated and evolved in a variety of software engineering contexts.\",\"PeriodicalId\":124452,\"journal\":{\"name\":\"International Symposium on Empirical Software Engineering and Measurement\",\"volume\":\"254 3\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-09-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Symposium on Empirical Software Engineering and Measurement\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2652524.2652568\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Symposium on Empirical Software Engineering and Measurement","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2652524.2652568","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Towards a semantic knowledge base on threats to validity and control actions in controlled experiments
[Context] Experiment planners need to be aware of relevant Threats to Validity (TTVs), so they can devise effective control actions or accept the risk. [Objective] The aim of this paper is to introduce a TTV knowledge base (KB) that supports experiment planners in identifying relevant TTVs in their research context and actions to control these TTVs. [Method] We identified requirements, designed and populated a TTV KB with data extracted during a systematic review: 63 TTVs and 149 control actions from 206 peer-reviewed published software engineering experiments. We conducted an initial proof of concept on the feasibility of using the TTV KB and analyzed its content. [Results] The proof of concept and content analysis provided indications that experiment planners can benefit from an extensible TTV KB for identifying relevant TTVs and control actions in their specific context. [Conclusions] The TTV KB should be further evaluated and evolved in a variety of software engineering contexts.