{"title":"嵌入式编译器的差异测试","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":"{\"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}","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}
RandIR: differential testing for embedded compilers
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.