{"title":"逻辑字节码缩减","authors":"Christian Gram Kalhauge, J. Palsberg","doi":"10.1145/3453483.3454091","DOIUrl":null,"url":null,"abstract":"Reducing a failure-inducing input to a smaller one is challenging for input with internal dependencies because most sub-inputs are invalid. Kalhauge and Palsberg made progress on this problem by mapping the task to a reduction problem for dependency graphs that avoids invalid inputs entirely. Their tool J-Reduce efficiently reduces Java bytecode to 24 percent of its original size, which made it the most effective tool until now. However, the output from their tool is often too large to be helpful in a bug report. In this paper, we show that more fine-grained modeling of dependencies leads to much more reduction. Specifically, we use propositional logic for specifying dependencies and we show how this works for Java bytecode. Once we have a propositional formula that specifies all valid sub-inputs, we run an algorithm that finds a small, valid, failure-inducing input. Our algorithm interleaves runs of the buggy program and calls to a procedure that finds a minimal satisfying assignment. Our experiments show that we can reduce Java bytecode to 4.6 percent of its original size, which is 5.3 times better than the 24.3 percent achieved by J-Reduce. The much smaller output is more suitable for bug reports.","PeriodicalId":20557,"journal":{"name":"Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Logical bytecode reduction\",\"authors\":\"Christian Gram Kalhauge, J. Palsberg\",\"doi\":\"10.1145/3453483.3454091\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Reducing a failure-inducing input to a smaller one is challenging for input with internal dependencies because most sub-inputs are invalid. Kalhauge and Palsberg made progress on this problem by mapping the task to a reduction problem for dependency graphs that avoids invalid inputs entirely. Their tool J-Reduce efficiently reduces Java bytecode to 24 percent of its original size, which made it the most effective tool until now. However, the output from their tool is often too large to be helpful in a bug report. In this paper, we show that more fine-grained modeling of dependencies leads to much more reduction. Specifically, we use propositional logic for specifying dependencies and we show how this works for Java bytecode. Once we have a propositional formula that specifies all valid sub-inputs, we run an algorithm that finds a small, valid, failure-inducing input. Our algorithm interleaves runs of the buggy program and calls to a procedure that finds a minimal satisfying assignment. Our experiments show that we can reduce Java bytecode to 4.6 percent of its original size, which is 5.3 times better than the 24.3 percent achieved by J-Reduce. The much smaller output is more suitable for bug reports.\",\"PeriodicalId\":20557,\"journal\":{\"name\":\"Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3453483.3454091\",\"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 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3453483.3454091","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Reducing a failure-inducing input to a smaller one is challenging for input with internal dependencies because most sub-inputs are invalid. Kalhauge and Palsberg made progress on this problem by mapping the task to a reduction problem for dependency graphs that avoids invalid inputs entirely. Their tool J-Reduce efficiently reduces Java bytecode to 24 percent of its original size, which made it the most effective tool until now. However, the output from their tool is often too large to be helpful in a bug report. In this paper, we show that more fine-grained modeling of dependencies leads to much more reduction. Specifically, we use propositional logic for specifying dependencies and we show how this works for Java bytecode. Once we have a propositional formula that specifies all valid sub-inputs, we run an algorithm that finds a small, valid, failure-inducing input. Our algorithm interleaves runs of the buggy program and calls to a procedure that finds a minimal satisfying assignment. Our experiments show that we can reduce Java bytecode to 4.6 percent of its original size, which is 5.3 times better than the 24.3 percent achieved by J-Reduce. The much smaller output is more suitable for bug reports.