Algorithmic Thinking: A Problem-Based Introduction

Zingaro, Daniel



A hands-on, problem-based introduction to building algorithms and data structures to solve problems with a computer.

Programming is about using a computer to solve problems, and algorithms and data structures are the building blocks of computer programs. For each problem that a programmer wants to solve, they employ an algorithm: a sequence of steps for solving the problem. Many books teach algorithms independently of specific problems, but this book uses careful explanations, examples, and arguments, rather than formal mathematics and proofs which make it difficult for you to connect what you are learning to what you can do with that learning. Algorithmic Thinking: A Problem-Based Introduction teaches you to use the best algorithms and data structures for a given situation by walking you through solving problems pulled from international programming competitions, such as how to determine whether snowflakes are unique; how to win a game in the minimum number of moves; how to find the number of ways to get to someone's house; how to escape a cave in as few steps as possible; and so on.

You'll tackle challenging topics like recursion, dynamic programming, graphs, greedy algorithms, heaps, hash tables, segment trees, and other data structures for efficiently handling data. The book contains no pseudocode: all code is written in C and is thoroughly explained in the text (C is a de facto programming language for programming competitions). By the end of the book, you should understand the importance of carefully working through a problem, and why it pays to organize data using data structures.


Dr. Daniel Zingaro is an award-winning Assistant Professor of Mathematical and Computational Sciences at the University of Toronto Mississauga, where he is well known for his uniquely interactive approach to teaching, and internationally recognized for his expertise in Active Learning.