{"title":"Unifying view of recent LALR(1) lookahead set algorithms","authors":"F. Ives","doi":"10.1145/12276.13324","DOIUrl":null,"url":null,"abstract":"Since the introduction of LALR parsing, several algorithms have been presented for the computation of the lookahead sets needed to produce an LALR parser. The algorithm in Aho and Ullman[1] has perhaps received the widest exposure. The recent algorithms by DeRemer and Pennello[2] and Park, Choe, and Chang[4] are the most efficient.\nA new algorithm has been developed from an algorithm originally based on the Aho and Ullman algorithm and subsequently modified to take advantage of the efficiencies introduced by the DeRemer and Pennello algorithm. The new algorithm performs better than the Park, Choe, and Chang algorithm, and both perform better than the DeRemer and Pennello algorithm. The reasons for the relative performances are easily understood when the algorithms are presented in a common light.","PeriodicalId":414056,"journal":{"name":"SIGPLAN Conferences and Workshops","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1986-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SIGPLAN Conferences and Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/12276.13324","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
Since the introduction of LALR parsing, several algorithms have been presented for the computation of the lookahead sets needed to produce an LALR parser. The algorithm in Aho and Ullman[1] has perhaps received the widest exposure. The recent algorithms by DeRemer and Pennello[2] and Park, Choe, and Chang[4] are the most efficient.
A new algorithm has been developed from an algorithm originally based on the Aho and Ullman algorithm and subsequently modified to take advantage of the efficiencies introduced by the DeRemer and Pennello algorithm. The new algorithm performs better than the Park, Choe, and Chang algorithm, and both perform better than the DeRemer and Pennello algorithm. The reasons for the relative performances are easily understood when the algorithms are presented in a common light.
自从引入LALR解析以来,已经提出了几种算法来计算生成LALR解析器所需的前瞻集。Aho和Ullman[1]中的算法可能得到了最广泛的曝光。最近由DeRemer和Pennello[2]以及Park, Choe, and Chang[4]提出的算法是最有效的。该算法最初基于Aho和Ullman算法,随后进行了修改,以利用DeRemer和Pennello算法引入的效率,从而开发了一种新的算法。新算法的性能优于Park、Choe、Chang算法,也优于DeRemer和Pennello算法。当这些算法以一种共同的方式呈现时,相对性能的原因很容易理解。