{"title":"Breaking parsers: mutation-based generation of programs with guaranteed syntax errors","authors":"Moeketsi Raselimo, J. Taljaard, B. Fischer","doi":"10.1145/3357766.3359542","DOIUrl":null,"url":null,"abstract":"Grammar-based test case generation has focused almost exclusively on generating syntactically correct programs (i.e., positive tests) from a context-free reference grammar but a positive test suite cannot detect when the unit under test accepts words outside the language (i.e., false positives). Here, we investigate the converse problem and describe two mutation-based approaches for generating programs with guaranteed syntax errors (i.e., negative tests). % Word mutation systematically modifies positive tests by deleting, inserting, substituting, and transposing tokens in such a way that at least one impossible token pair emerges. % Rule mutation applies such operations to the symbols of the right-hand sides of productions in such a way that each derivation that uses the mutated rule yields a word outside the language.","PeriodicalId":354325,"journal":{"name":"Proceedings of the 12th ACM SIGPLAN International Conference on Software Language Engineering","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 12th ACM SIGPLAN International Conference on Software Language Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3357766.3359542","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
Grammar-based test case generation has focused almost exclusively on generating syntactically correct programs (i.e., positive tests) from a context-free reference grammar but a positive test suite cannot detect when the unit under test accepts words outside the language (i.e., false positives). Here, we investigate the converse problem and describe two mutation-based approaches for generating programs with guaranteed syntax errors (i.e., negative tests). % Word mutation systematically modifies positive tests by deleting, inserting, substituting, and transposing tokens in such a way that at least one impossible token pair emerges. % Rule mutation applies such operations to the symbols of the right-hand sides of productions in such a way that each derivation that uses the mutated rule yields a word outside the language.