{"title":"通过模糊测试找到规范盲点","authors":"Ru Ji, Meng Xu","doi":"10.1109/SP46215.2023.10179438","DOIUrl":null,"url":null,"abstract":"A formally verified program is only as correct as its specifications (SPEC). But how to assure that the SPEC is complete and free of loopholes? This paper presents Fast, short for Fuzzing-Assisted Specification Testing, as a potential answer. The key insight is to exploit and synergize the \"redundancy\" and \"diversity\" in formally verified programs for cross-checking. Specifically, within the same codebase, SPEC, implementation (CODE), and test suites are all derived from the same set of business requirements. Therefore, if some intention is captured in CODE and test case but not in SPEC, this is a strong indication that there is a blind spot in SPEC.Fast examines the SPEC for incompleteness issues in an automated way: it first locates SPEC gaps via mutation testing, i.e., by checking whether a CODE variant conforms to the original SPEC. If so, Fast further leverages the test suites to infer whether the gap is introduced by intention or by mistake. Depending on the codebase size, Fast may choose to generate CODE variants in either an enumerative or evolutionary way. Fast is applied to two open-source codebases that feature formal verification and helps to confirm 13 and 21 blind spots in their SPEC respectively. This highlights the prevalence of SPEC incompleteness in real-world applications.","PeriodicalId":439989,"journal":{"name":"2023 IEEE Symposium on Security and Privacy (SP)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Finding Specification Blind Spots via Fuzz Testing\",\"authors\":\"Ru Ji, Meng Xu\",\"doi\":\"10.1109/SP46215.2023.10179438\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A formally verified program is only as correct as its specifications (SPEC). But how to assure that the SPEC is complete and free of loopholes? This paper presents Fast, short for Fuzzing-Assisted Specification Testing, as a potential answer. The key insight is to exploit and synergize the \\\"redundancy\\\" and \\\"diversity\\\" in formally verified programs for cross-checking. Specifically, within the same codebase, SPEC, implementation (CODE), and test suites are all derived from the same set of business requirements. Therefore, if some intention is captured in CODE and test case but not in SPEC, this is a strong indication that there is a blind spot in SPEC.Fast examines the SPEC for incompleteness issues in an automated way: it first locates SPEC gaps via mutation testing, i.e., by checking whether a CODE variant conforms to the original SPEC. If so, Fast further leverages the test suites to infer whether the gap is introduced by intention or by mistake. Depending on the codebase size, Fast may choose to generate CODE variants in either an enumerative or evolutionary way. Fast is applied to two open-source codebases that feature formal verification and helps to confirm 13 and 21 blind spots in their SPEC respectively. This highlights the prevalence of SPEC incompleteness in real-world applications.\",\"PeriodicalId\":439989,\"journal\":{\"name\":\"2023 IEEE Symposium on Security and Privacy (SP)\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE Symposium on Security and Privacy (SP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SP46215.2023.10179438\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE Symposium on Security and Privacy (SP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SP46215.2023.10179438","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Finding Specification Blind Spots via Fuzz Testing
A formally verified program is only as correct as its specifications (SPEC). But how to assure that the SPEC is complete and free of loopholes? This paper presents Fast, short for Fuzzing-Assisted Specification Testing, as a potential answer. The key insight is to exploit and synergize the "redundancy" and "diversity" in formally verified programs for cross-checking. Specifically, within the same codebase, SPEC, implementation (CODE), and test suites are all derived from the same set of business requirements. Therefore, if some intention is captured in CODE and test case but not in SPEC, this is a strong indication that there is a blind spot in SPEC.Fast examines the SPEC for incompleteness issues in an automated way: it first locates SPEC gaps via mutation testing, i.e., by checking whether a CODE variant conforms to the original SPEC. If so, Fast further leverages the test suites to infer whether the gap is introduced by intention or by mistake. Depending on the codebase size, Fast may choose to generate CODE variants in either an enumerative or evolutionary way. Fast is applied to two open-source codebases that feature formal verification and helps to confirm 13 and 21 blind spots in their SPEC respectively. This highlights the prevalence of SPEC incompleteness in real-world applications.