{"title":"图形化领域建模环境的推荐器设计","authors":"Andrej Dyck, A. Ganser, H. Lichter","doi":"10.5220/0004701802910299","DOIUrl":null,"url":null,"abstract":"Recommender systems for source code artifacts are newly emerging and are now successfully supporting programmers. Their underlying knowledge bases, recommender algorithms, and user interfaces are well studied. Integrated into the development environment, they do a fairly good job in reducing complexity and development time.","PeriodicalId":336046,"journal":{"name":"2014 2nd International Conference on Model-Driven Engineering and Software Development (MODELSWARD)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"On designing recommenders for graphical domain modeling environments\",\"authors\":\"Andrej Dyck, A. Ganser, H. Lichter\",\"doi\":\"10.5220/0004701802910299\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recommender systems for source code artifacts are newly emerging and are now successfully supporting programmers. Their underlying knowledge bases, recommender algorithms, and user interfaces are well studied. Integrated into the development environment, they do a fairly good job in reducing complexity and development time.\",\"PeriodicalId\":336046,\"journal\":{\"name\":\"2014 2nd International Conference on Model-Driven Engineering and Software Development (MODELSWARD)\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-01-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 2nd International Conference on Model-Driven Engineering and Software Development (MODELSWARD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5220/0004701802910299\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 2nd International Conference on Model-Driven Engineering and Software Development (MODELSWARD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0004701802910299","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On designing recommenders for graphical domain modeling environments
Recommender systems for source code artifacts are newly emerging and are now successfully supporting programmers. Their underlying knowledge bases, recommender algorithms, and user interfaces are well studied. Integrated into the development environment, they do a fairly good job in reducing complexity and development time.