{"title":"大型程序高效数据流分析的实现技术","authors":"Darren C. Atkinson, W. Griswold","doi":"10.1109/ICSM.2001.972711","DOIUrl":null,"url":null,"abstract":"Many software engineering tools such as program slicers must perform data-flow analysis in order to extract necessary information from the program source. These tools typically borrow much of their implementation from optimizing compilers. However, since these tools are expected to analyze programs in their entirety, rather than functions in isolation, the time and space performance of the dataflow analyses are of major concern. We present techniques that reduce the time and space required to perform dataflow analysis of large programs. We have used these techniques to implement an efficient program slicing tool for C programs and have computed slices of programs with more than 100,000 lines of code.","PeriodicalId":160032,"journal":{"name":"Proceedings IEEE International Conference on Software Maintenance. ICSM 2001","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"48","resultStr":"{\"title\":\"Implementation techniques for efficient data-flow analysis of large programs\",\"authors\":\"Darren C. Atkinson, W. Griswold\",\"doi\":\"10.1109/ICSM.2001.972711\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Many software engineering tools such as program slicers must perform data-flow analysis in order to extract necessary information from the program source. These tools typically borrow much of their implementation from optimizing compilers. However, since these tools are expected to analyze programs in their entirety, rather than functions in isolation, the time and space performance of the dataflow analyses are of major concern. We present techniques that reduce the time and space required to perform dataflow analysis of large programs. We have used these techniques to implement an efficient program slicing tool for C programs and have computed slices of programs with more than 100,000 lines of code.\",\"PeriodicalId\":160032,\"journal\":{\"name\":\"Proceedings IEEE International Conference on Software Maintenance. ICSM 2001\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-11-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"48\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings IEEE International Conference on Software Maintenance. ICSM 2001\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSM.2001.972711\",\"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 IEEE International Conference on Software Maintenance. ICSM 2001","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSM.2001.972711","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Implementation techniques for efficient data-flow analysis of large programs
Many software engineering tools such as program slicers must perform data-flow analysis in order to extract necessary information from the program source. These tools typically borrow much of their implementation from optimizing compilers. However, since these tools are expected to analyze programs in their entirety, rather than functions in isolation, the time and space performance of the dataflow analyses are of major concern. We present techniques that reduce the time and space required to perform dataflow analysis of large programs. We have used these techniques to implement an efficient program slicing tool for C programs and have computed slices of programs with more than 100,000 lines of code.