100 Books Like The Art of Computer Programming

This book is not about computing, but it is relevant in an indirect way. I love this book, since it is written in such an engaging style and illustrates with many examples that math is not a dry subject to be practiced only by mathematicians but helps everyone to solve real-world problems. The book shows how important it is to be precise in describing problems and that applying a little mathematical rigor goes a long way in solving them. Ellenberg describes mathematics as the “extension of common sense by other means.” In a similar way, I view computer science as the extension of problem-solving methods (aka “algorithms”) by other means. 

Polya was a great mathematician who knew what counted (after all, he made major contributions to combinatorics, the mathematics of counting). He thought hard about what he was doing when working on problems in mathematics, developing a mental process that lead to creative breakthroughs and solutions. Polya’s problem-solving method is broadly applicable to domains other than mathematics, and this book features many nice puzzles to improve your thinking.

Algorithm design is challenging because it often requires flashes of sudden insight which seem to come out of the blue. But there is a way of thinking about problems that make such flashes more likely to happen. I try to teach this thought process in my books, but Polya got there first.

I always find myself applying algorithmic thinking in my everyday life—it affects the way I put away dishes, navigate to the store, and organize my to-do lists. And I think others could benefit from that mindset.

So, when I read this book, my reaction was "Yes! That's what I want people to know. I just wish I could have said it that well!" The authors (who I know, but didn't know they wrote a book together), did a fantastic job of selecting algorithms with deep human connections. Really! And they explain them just right, without getting too mathematical but while still hitting the key ideas with clarity and accuracy. Fantastic!

Ulam was a Polish mathematical prodigy, publishing significant mathematics by the time he was 20. He was part of the rich Polish math community centered around Stefan Banach. Unlike most, he was heading to the United States in 1939 (with his younger brother) when Germany invaded Poland. All the rest of his family were murdered by the Nazis. He on the other hand ended up in Los Alamos, providing critical help on the Manhattan Project. Later in life, he wrote this book, his autobiography. Based on his history, one could well think that it would be a book full of tragic grief. Instead, it is a pean to the joys of doing mathematics and of living a life full of mathematics, without downplaying the horrors of the mid-twentieth century. 

This multi-volume book is, for me, a masterpiece that goes far beyond just coding or algorithms or data structures, and serves as a profound exploration of algorithmic thinking and computer science's theoretical foundations, going deeply into the performance of algorithms and the behavior of data structures.

Knuth's meticulous approach, coupled with his clear and engaging prose (with occasional touches of humor) clearly explains complex concepts, and shows a deep understanding of the artistry inherent in solving computational problems.

Bill Gates said that anybody who went through all its volumes would get a job at his company, and I surely agree! I would recommend this book both for novice or seasoned programmers, because you will always find invaluable insights in it.

This book is essential in that it follows a systematic and scientific approach to software development, advocating for clarity in expressing algorithms, providing a rigorous framework for designing and reasoning about programs, and, fundamentally, always focusing on formal methods and mathematical techniques to ensure correctness and efficiency in programming code.

Most importantly, the book doesn’t just show you how to prove programs correct, but also teaches how to arrive from a definition to an efficient and correct solution, so I would recommend this to every developer.

This is the definitive book series on algorithms and the core of computer programming.

Unlike most such books, Knuth is a real programmer, deep into the details of the craft, to the point of creating his own assembler language and typesetting generation system. It’s partly the substance of the algorithms and their analysis, but even more is the way he models a way of thinking about and solving complexity that makes this a must-read series.

Smalltalk is not as common or popular as it once was, but the influence its design had on programming is hard to overstate.

Reading this book has changed how I think about object orientation, and how I design systems, learning the patterns of Smalltalk makes it clear what object oriented design is really intended to achieve.

Okay, hear me out. Yes, this book was published in 2007. Yes, it’s ostensibly about ActionScript, the coding language in Flash, which no one uses anymore. But you won’t use this book to learn ActionScript or Flash: You’ll use it to learn how to make things move with code, in any language. You’ll skip over the ActionScript-specific parts in favor of the lucid explanations and helpful illustrations. Your visual brain will appreciate seeing how sines, cosines, and tangents are relevant—and necessary!—to make digital things move. (Your heart will wish your brain had paid better attention in trigonometry class years earlier, but hey, no regrets!) The chapters “Trigonometry for Animation” and “Velocity and Acceleration” alone are worth the purchase price.

If you want your interactive graphics to feel like they are real objects—real things moving around on the screen—then you have to learn how to mimic the natural world. For an object to feel like it has weight, you have to mimic gravity. For a flock of birds to feel real, you have to mimic how real birds swarm in the sky. Yes, this does involve little math. But fortunately, Dan is a superstar teacher, and he will gently walk you through (a) the math and (b) how to translate that math into code.

Speaking of code, this book uses Processing.js, which is an older adaptation of original Processing to JavaScript. That said, the techniques are all equally applicable to modern-day Processing and p5.js.