{"title":"测试流图的可简化性","authors":"R. Tarjan","doi":"10.1145/800125.804040","DOIUrl":null,"url":null,"abstract":"Many problems in program optimization have been solved by applying a technique called interval analysis to the flow graph of the program. A flow graph which is susceptible to this type of analysis is called reducible. This paper describes an algorithm for testing whether a flow graph is reducible. The algorithm uses depth-first search to reveal the structure of the flow graph and a good method for computing disjoint set unions to determine reducibility from the search information. When the algorithm is implemented on a random access computer, it requires O(E log* E) time to analyze a graph with E edges, where log* x = min{i/logix≤1}. The time bound compares favorably with the O(E log E) bound of a previously known algorithm.","PeriodicalId":242946,"journal":{"name":"Proceedings of the fifth annual ACM symposium on Theory of computing","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1973-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"251","resultStr":"{\"title\":\"Testing flow graph reducibility\",\"authors\":\"R. Tarjan\",\"doi\":\"10.1145/800125.804040\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Many problems in program optimization have been solved by applying a technique called interval analysis to the flow graph of the program. A flow graph which is susceptible to this type of analysis is called reducible. This paper describes an algorithm for testing whether a flow graph is reducible. The algorithm uses depth-first search to reveal the structure of the flow graph and a good method for computing disjoint set unions to determine reducibility from the search information. When the algorithm is implemented on a random access computer, it requires O(E log* E) time to analyze a graph with E edges, where log* x = min{i/logix≤1}. The time bound compares favorably with the O(E log E) bound of a previously known algorithm.\",\"PeriodicalId\":242946,\"journal\":{\"name\":\"Proceedings of the fifth annual ACM symposium on Theory of computing\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1973-04-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"251\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the fifth annual ACM symposium on Theory of computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/800125.804040\",\"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 fifth annual ACM symposium on Theory of computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/800125.804040","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 251
摘要
应用区间分析技术对程序流程图进行分析,解决了程序优化中的许多问题。易于进行这种分析的流图称为可约流图。本文描述了一种检验流图是否可约的算法。该算法使用深度优先搜索来揭示流图的结构,并使用一种计算不相交集并的好方法来从搜索信息中确定可约性。当算法在随机存取计算机上实现时,分析一个有E条边的图需要O(E log* E)时间,其中log* x = min{i/logix≤1}。与以前已知的算法的O(E log E)界相比,该时间界限更为有利。
Many problems in program optimization have been solved by applying a technique called interval analysis to the flow graph of the program. A flow graph which is susceptible to this type of analysis is called reducible. This paper describes an algorithm for testing whether a flow graph is reducible. The algorithm uses depth-first search to reveal the structure of the flow graph and a good method for computing disjoint set unions to determine reducibility from the search information. When the algorithm is implemented on a random access computer, it requires O(E log* E) time to analyze a graph with E edges, where log* x = min{i/logix≤1}. The time bound compares favorably with the O(E log E) bound of a previously known algorithm.