Introduction to Algorithms is a math book written by four authorâ€™s named Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein. The work of these authors is famous worldwide and the book has been and is still used as a textbook in many universities around the world. Even when writing research papers, many graduates cite the references from this boom and to date, 8900 references have been sited from the book. The book sold over half a million copies in the two decades following its publishing.

## Introduction to Algorithms Pdf Review:

The book is fit for all environments whether it is an educational one or a professional one. The authors have tried to make this book as helpful for everyone alike as possible. Each chapter focuses on a single algorithm and two major things about each algorithm are discussed. One of these is the area in which the algorithm is applied and the other is the designing techniques.

## Introduction to Algorithms Pdf Features:

• The book has many editions with the first one ever being published in 1990.
• In the book, the authors have used Pseudocode as the language for algorithms. They have not used any specific programming language in the book.
• The book talks about the application of algorithms and their importance in the field of math

• Foundations
• 1 The Role of Algorithms in Computing
• 2 Getting Started
• 3 Growth of Functions
• 4 Divide-and-Conquer
• 5 Probabilistic Analysis and Randomized Algorithms
• II Sorting and Order Statistics
• 6 Heapsort
• 7 Quicksort
• 8 Sorting in Linear Time
• 9 Medians and Order Statistics
• III Data Structures
• 10 Elementary Data Structures
• 11 Hash Tables
• 12 Binary Search Trees
• 13 Red-Black Trees
• 14 Augmenting Data Structures
• IV Advanced Design and Analysis Techniques
• 15 Dynamic Programming
• 16 Greedy Algorithms
• 17 Amortized Analysis
• 18 B-Trees
• 19 Fibonacci Heaps
• 20 Van Emde Boas Trees
• 21 Data Structures for Disjoint Sets
• VI Graph Algorithms
• 22 Elementary Graph Algorithms
• 23 Minimum Spanning Trees
• 24 Single-Source Shortest Paths
• 25 All-Pairs Shortest Paths
• 26 Maximum Flow
• VII Selected Topics
• 28 Matrix Operations
• 29 Linear Programming
• 30 Polynomials and the FFT
• 31 Number-Theoretic Algorithms
• 32 String Matching
• 33 Computational Geometry
• 34 NP-Completeness
• 35 Approximation Algorithms
• VIII Appendix: Mathematical Background
• A Summations
• B Sets, Etc.
• C Counting and Probability
• D Matrices