Data Structure Practice: for Collegiate Programming Contests and Education

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