文件名称：Data.Structure.Practice.for.Collegiate.Programming.Contests.and.Education
文件大小：12.2MB
文件格式：PDF
更新时间：2019-03-15 08:08:49
Data Structure
Combining knowledge with strategies, Data Structure Practice for Collegiate Programming Contests and Education presents the first comprehensive book on data structure in programming contests. This book is designed for training collegiate programming contest teams in the nuances of data structure and for helping college students in computer-related majors to gain deeper understanding of data structure. Based on successful experiences in many world-level contests, the book includes 204 typical problems and detailed analyses selected from the ACM International Collegiate Programming Contest and other major programming contests since 1990. It is divided into four sections that focus on: Fundamental programming skills Experiments for linear lists Experiments for trees Experiments for graphs Each chapter contains a set of problems and includes hints. The book also provides test data for most problems as well as sources and IDs for online judgments that help with improving programming skills. Introducing a multi-options model and considerations of context, Data Structure Practice for Collegiate Programming Contests and Education encourages students to think creatively in solving programming problems. By taking readers through practical contest problems from analysis to implementation, it provides a complete source for enhancing understanding and polishing skills in programming. Table of Contents Section I: Fundamental Programming Skills Chapter 1: Practice for Simple Computing Chapter 2: Simple Simulation Chapter 3: Simple Recursion Section II: Experiments for Linear Lists Chapter 4: Linear Lists Accessed Directly Chapter 5: Applications of Linear Lists for Sequential Access Chapter 6: Generalized List Using Indexes Chapter 7: Sort of Linear Lists Section III: Experiments for Trees Chapter 8: Programming by Tree Structure Chapter 9: Applications of Binary Trees Chapter 10: Applications of Classical Trees Section IV: Experiments for Graphs Chapter 11: Applications of Graph Traversal Chapter 12: Algorithms of Minimum Spanning Trees Chapter 13: Algorithms of Best Paths Chapter 14: Algorithms of Bipartite Graphs and Flow Networks