Algorithms and data structures are the core of computer science and an important tool in other fields like statistics. A commodity algorithm is like a commodity in economics: it's correct, easy to understand, applicable to many problems, efficient, and free of intellectual property claims. This book covers all commodity algorithms and data structures learned in an algorithms class and many that aren't including randomized algorithms, large number arithmetic, external memory algorithms, numerical methods, optimization, string algorithms, and data compression.

Each algorithm and data structure is described clearly, completely, and concisely with text and full tested C++ code. Most descriptions have examples, illustrations, performance analysis, use cases, and suggestions for optimizations and extensions.

Many topics in this book appear only in specialized books and papers, including garbage-collecting freelists, collections of random number generators and hash functions for different use cases, priority queues that allow indexing, cyclic redundancy check algorithm, simplex method for linear programming, efficient dictionaries for variable length keys, simulated annealing, Monte Carlo method, and algorithms for reinforcement learning. This is the book the author wishes he had when he started studying algorithms.