{"title":"Complementing metaheuristic search with higher abstraction techniques","authors":"Frank R. Burton, Simon M. Poulding","doi":"10.1109/CMSBSE.2013.6604436","DOIUrl":null,"url":null,"abstract":"Search-Based Software Engineering and Model-Driven Engineering are both innovative approaches to software engineering. The premise of Search-Based Software Engineering is to reformulate engineering tasks as optimisation problems that can be solved using metaheuristic search techniques. Model-Driven Engineering aims to apply greater levels of abstraction to software engineering problems. In this paper, it is argued that these two approaches are complementary and that both research fields can make further progress by applying techniques from the other. We suggest ways in which synergies between the fields can be exploited.","PeriodicalId":193450,"journal":{"name":"2013 1st International Workshop on Combining Modelling and Search-Based Software Engineering (CMSBSE)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 1st International Workshop on Combining Modelling and Search-Based Software Engineering (CMSBSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CMSBSE.2013.6604436","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
Search-Based Software Engineering and Model-Driven Engineering are both innovative approaches to software engineering. The premise of Search-Based Software Engineering is to reformulate engineering tasks as optimisation problems that can be solved using metaheuristic search techniques. Model-Driven Engineering aims to apply greater levels of abstraction to software engineering problems. In this paper, it is argued that these two approaches are complementary and that both research fields can make further progress by applying techniques from the other. We suggest ways in which synergies between the fields can be exploited.