Data structure practice : for collegiate programming contests and education
著者
書誌事項
Data structure practice : for collegiate programming contests and education
CRC Press, c2016
- : hardback
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注記
Includes bibliographical references (p. 489) and index (p.491-495)
内容説明・目次
内容説明
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.
目次
FUNDAMENTAL PROGRAMMING SKILLS. Practice for Simple Computing. Simple Simulation. Simple Recursion. EXPERIMENTS FOR LINEAR LISTS. Linear Lists Accessed Directly. Applications of Linear Lists for Sequential Access. Generalized List Using Indexes. Sort of Linear Lists. EXPERIMENTS FOR TREES. Programming by Tree Structure. Applications of Binary Trees. Applications of Classical Trees. EXPERIMENTS FOR GRAPHS. Applications of Graph Traversal. Algorithms of Minimum Spanning Trees. Algorithms of Best Paths. Algorithms of Bipartite Graphs and Flow Networks.
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