{"title":"Random testing in Isabelle/HOL","authors":"Stefan Berghofer, T. Nipkow","doi":"10.1109/SEFM.2004.36","DOIUrl":null,"url":null,"abstract":"When developing non-trivial formalizations in a theorem prover, a considerable amount of time is devoted to \"debugging\" specifications and conjectures by failed proof attempts. To detect such problems early in the proof and save development time, we have extended the Isabelle theorem prover with a tool for testing specifications by evaluating propositions under an assignment of random values to free variables. Distribution of the test data is optimized via mutation testing. The technical contributions are an extension of earlier work with inductive definitions and a generic method for randomly generating elements of recursive datatypes.","PeriodicalId":207271,"journal":{"name":"Proceedings of the Second International Conference on Software Engineering and Formal Methods, 2004. SEFM 2004.","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"113","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Second International Conference on Software Engineering and Formal Methods, 2004. SEFM 2004.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SEFM.2004.36","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 113
Abstract
When developing non-trivial formalizations in a theorem prover, a considerable amount of time is devoted to "debugging" specifications and conjectures by failed proof attempts. To detect such problems early in the proof and save development time, we have extended the Isabelle theorem prover with a tool for testing specifications by evaluating propositions under an assignment of random values to free variables. Distribution of the test data is optimized via mutation testing. The technical contributions are an extension of earlier work with inductive definitions and a generic method for randomly generating elements of recursive datatypes.