{"title":"RandIR: differential testing for embedded compilers","authors":"Georg Ofenbeck, Tiark Rompf, Markus Püschel","doi":"10.1145/2998392.2998397","DOIUrl":null,"url":null,"abstract":"This paper describes RandIR, a tool for differential testing of compilers using random instances of a given intermediate representation (IR). RandIR assumes no fixed target language but instead supports extensible IR-definitions through an internal IR-independent representation of operations. This makes it particularly well suited to test embedded compilers for multi-stage programming, which is our main use case. The ideas underlying our work, however, are more generally applicable. RandIR is able to automatically simplify failing instances of a test, a technique commonly referred to as shrinking. This enables testing with large random IR samples, thus increasing the odds of detecting a buggy behavior, while still being able to simplify failing instances to human-readable code.","PeriodicalId":269542,"journal":{"name":"Proceedings of the 2016 7th ACM SIGPLAN Symposium on Scala","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2016 7th ACM SIGPLAN Symposium on Scala","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2998392.2998397","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17
Abstract
This paper describes RandIR, a tool for differential testing of compilers using random instances of a given intermediate representation (IR). RandIR assumes no fixed target language but instead supports extensible IR-definitions through an internal IR-independent representation of operations. This makes it particularly well suited to test embedded compilers for multi-stage programming, which is our main use case. The ideas underlying our work, however, are more generally applicable. RandIR is able to automatically simplify failing instances of a test, a technique commonly referred to as shrinking. This enables testing with large random IR samples, thus increasing the odds of detecting a buggy behavior, while still being able to simplify failing instances to human-readable code.