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  • 用一门面向对象语言建立一个针对LL(1)文法分析构造演示器

    用一门面向对象语言建立一个针对LL(1)文法分析构造演示器,输入定义好的文法,进行分析后在内存中建立其存储结构,判断其能用LL(1)文法分析后,建立其分析过程。 为此我们将本任务分解为以下内容: (1)文法的建立; (2)上下文无关文法的判定; (3)消除文法中一切左递归的算法; (4)文法二义性的判定; (5)LL(1)文法的判定; (6)消除直接左递归; (7)消除间接左递归; (8)直接左公因子的改造; (9)间接左公因子的改造; (10)递归子程序的构造; (11)根据布尔矩阵求Follow集; (12)能导出ε的非终结符; (13)根据定义构造First集; (14)根据关系图构造First集; (15)根据定义构造Follow集; (16)根据关系图构造Follow集; (17)Select集的构造; (18)预测分析表的构造; (19)总控程序的构造; (20)语法树的演示; (21)根据总控程序输出语法树; (22)根据布尔矩阵求First集。 我所要完成的任务是 语法树的演示。

    标签: LL 对象 语言

    上传时间: 2016-07-30

    上传用户:kelimu

  • 编译原理课程设计

    编译原理课程设计,LL(1)方法,用FIRST()和FOLLOW(),SELECT(),以及预测分析表

    标签: 编译原理

    上传时间: 2013-12-24

    上传用户:hphh

  • hh lecture has based hardware, embedded development environment construction, embedded programme sel

    hh lecture has based hardware, embedded development environment construction, embedded programme selection, embedded industry overview and so on.

    标签: embedded construction development environment

    上传时间: 2013-12-21

    上传用户:冇尾飞铊

  • The task of clustering Web sessions is to group Web sessions based on similarity and consists of max

    The task of clustering Web sessions is to group Web sessions based on similarity and consists of maximizing the intra- group similarity while minimizing the inter-group similarity. The first and foremost question needed to be considered in clustering W b sessions is how to measure the similarity between Web sessions.However.there are many shortcomings in traditiona1 measurements.This paper introduces a new method for measuring similarities between Web pages that takes into account not only the URL but also the viewing time of the visited web page.Yhen we give a new method to measure the similarity of Web sessions using sequence alignment and the similarity of W eb page access in detail Experiments have proved that our method is valid and e币cient.

    标签: sessions clustering similarity Web

    上传时间: 2014-01-11

    上传用户:songrui

  • 輕易學好C++編程技巧 - 進楷 (香港科技大學筆記 19課) 內容包括 1) base C++ review, 2) Pointers and Dynamic Objects, 3) R

    輕易學好C++編程技巧 - 進楷 (香港科技大學筆記 19課) 內容包括 1) base C++ review, 2) Pointers and Dynamic Objects, 3) Recursion,Linked Lists, 4) Stacks and Queues, 5) Algorithm Analysis, 6) Insertion Sort and Mergesort, 7) Quicksort, 8) Heaps and Heapsort, 9) Lower Bound of Sorting and Radix Sort, 10) Binary Trees and Binary Search Trees 11) AVL Trees, 12) B+ Trees 13) Graphs and Breadth-First Search 14) Depth-First Search 15) Connected Components, Directed Graphs, 16) Topological Sort 17) Hashing 18) Pattern Matching 19) Additional Review

    标签: Pointers Dynamic Objects review

    上传时间: 2014-10-10

    上传用户:chfanjiang

  • 使用MFC实现编译原理词法分析器

    使用MFC实现编译原理词法分析器,里面包括求first集和follow集

    标签: MFC 编译原理 分析器

    上传时间: 2016-08-10

    上传用户:lz4v4

  • This is a simple GPS tracer developed for Window Mobile 2005/2003 on Compact Framework 2.0 SDK. So f

    This is a simple GPS tracer developed for Window Mobile 2005/2003 on Compact Framework 2.0 SDK. So first of all, you need VisualStudio 2005 and Windows Mobile CE 5 SDK. You can develop it on emulator devices or on a real device. As you can see in that photo, I developed that application on a read device: the great Asus MyPal 636N.

    标签: Framework developed Compact Mobile

    上传时间: 2016-08-11

    上传用户:gxf2016

  • LL1文法的实现

    LL1文法的实现,先输入语法规则,之后求出FIRST和FOLLOW,最后给出预测分析表。

    标签: LL1

    上传时间: 2013-12-28

    上传用户:q123321

  • FASTICA can be called with numerous optional arguments. Optional arguments are given in parameter pa

    FASTICA can be called with numerous optional arguments. Optional arguments are given in parameter pairs, so that first argument is the name of the parameter and the next argument is the value for that parameter. Optional parameter pairs can be given in any order.

    标签: arguments parameter Optional numerous

    上传时间: 2014-08-18

    上传用户:2525775

  • Recent advances in experimental methods have resulted in the generation of enormous volumes of data

    Recent advances in experimental methods have resulted in the generation of enormous volumes of data across the life sciences. Hence clustering and classification techniques that were once predominantly the domain of ecologists are now being used more widely. This book provides an overview of these important data analysis methods, from long-established statistical methods to more recent machine learning techniques. It aims to provide a framework that will enable the reader to recognise the assumptions and constraints that are implicit in all such techniques. Important generic issues are discussed first and then the major families of algorithms are described. Throughout the focus is on explanation and understanding and readers are directed to other resources that provide additional mathematical rigour when it is required. Examples taken from across the whole of biology, including bioinformatics, are provided throughout the book to illustrate the key concepts and each technique’s potential.

    标签: experimental generation advances enormous

    上传时间: 2016-10-23

    上传用户:wkchong