{"title":"破坏解析器:基于突变的程序生成,保证有语法错误","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":"{\"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}","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}
Breaking parsers: mutation-based generation of programs with guaranteed syntax errors
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.