{"title":"Graph rewriting and transformation (GReAT): a solution for the model integrated computing (MIC) bottleneck","authors":"Aditya Agrawal","doi":"10.1109/ASE.2003.1240339","DOIUrl":null,"url":null,"abstract":"Graph grammars and transformations (GGT) have been a field of theoretical study for over two decades. However, it has produced only a handful of practical implementations. GGT needs a widely used practical application to exploit its potential. On the other hand model integrated computing (MIC) has grown from the practical standpoint and is widely used and recognized in both industry and practice today. In the MIC approach, developing model-interpreters is time consuming and costly, proving to be a bottleneck. This reduces MIC's reach and impact on the programming community. In this paper I propose to use GGT methodologies to solve MIC's bottleneck problem. The solution should place the MIC technology such that it can play a defining role in the next generation of high-level programming languages.","PeriodicalId":114604,"journal":{"name":"18th IEEE International Conference on Automated Software Engineering, 2003. Proceedings.","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"55","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"18th IEEE International Conference on Automated Software Engineering, 2003. Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASE.2003.1240339","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 55
Abstract
Graph grammars and transformations (GGT) have been a field of theoretical study for over two decades. However, it has produced only a handful of practical implementations. GGT needs a widely used practical application to exploit its potential. On the other hand model integrated computing (MIC) has grown from the practical standpoint and is widely used and recognized in both industry and practice today. In the MIC approach, developing model-interpreters is time consuming and costly, proving to be a bottleneck. This reduces MIC's reach and impact on the programming community. In this paper I propose to use GGT methodologies to solve MIC's bottleneck problem. The solution should place the MIC technology such that it can play a defining role in the next generation of high-level programming languages.