100 books like The Science of Programming

This book is different from the others I recommended, because its focus is not really on creating algorithms, but rather on how to improve code with a systematic process, keeping functionality but enhancing quality.

The author shows several practical techniques that he applies to real-world problems and empower you to elevate your code's quality and adapt it seamlessly to changing needs. It's not just about writing code; it's about becoming a more effective and confident developer.

I consider this book a companion on the journey to mastering the craft of coding. With it, you’ll always be able to achieve higher-quality code, no matter the original version of the code.

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 thin but quite fulfilling book is a compact yet profound exploration of proven program correctness, probably one of the first texts to focus on that topic.

Dijkstra's emphasis on mathematical rigor and disciplined thinking reshapes how programmers approach problem-solving. The author imparts essential principles of program construction, advocating for clarity and precision in code, and leading to cultivating a disciplined mindset, and fostering a deep appreciation for the art and science of programming.

Despite its age, all its knowledge is fully valid, and I’d give the book to every programmer so they can reach a higher level of quality.

Of all the books I recommend, this is practically a sort of personal bible, which I very frequently consult.

This book doesn't just show you how to code; with realistic patterns and real-world examples, it's like having experienced mentors guiding your every keystroke. These patterns aren't just snippets; they're blueprints for building robust, flexible software.

I think the book is practically mandatory for all developers, novice or seasoned. It transformed how I approach problems, teaching me techniques I use daily in systems design and development.

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.

Knuth’s unique mix of playfulness and rigor came to define computer science as an intellectual discipline: computer science didn’t really have anything to do with computers, but everything to do with a particular way of seeing the world.  Just browse and wonder at the beauty and precision achieved in these books.   

Volume 3 (Sorting and Searching) is my personal favorite, and I encourage you to start there. During the pandemic, I finally got around to reading Volume 4A (Combinatorial Algorithms), which was published thirty plus years after Volume 3. It was the same feeling I had watching the movie The Phantom Menace years after growing up with the original Star Wars trilogy. I had forgotten just how unique and distinctive Knuth’s Art of Computer Programming is.

Michael Lopp, or Rands, as he is commonly known online, has been sharing his knowledge as a software manager for years, mainly through his blog. He is one of the most insightful voices about the art of management in a software environment, and even if you are not a manager yourself (and don’t want to become one), will make you understand and better collaborate with your own manager, and be ready when you need to lead a team or understand how it is to work with other humans.

Yes, it’s a textbook, albeit a particularly well-written one. You may already have it on your shelf, if you’ve taken a programming class or two.

I’m way too old to have used CLRS as a textbook, though! For me, it’s an effectively bottomless collection of neat little ideas—an easy-to-describe problem, then a series of increasingly clever ways to solve that problem. How often do I end up using one of those algorithms? Not very often! But every time I read the description of an algorithm, I get a nugget of pure joy from the “aha” moment when I first understand how it works.

The most important unanswered question in computer science has a huge public relations problem. Back in the 1970s, this question became known as “P=NP?”—and who could write an exciting book about that? Luckily for us, Lance Fortnow can. As one of the world’s foremost experts on P-vs-NP, he takes us on a wild and truly accessible ride through the most important question about computing. I’ve seen many attempts at making “P=NP?” accessible/understandable/intriguing for non-experts. But Fortnow nails it like nobody else, reformulating P-vs-NP as a search for one of the golden tickets in Charlie and the Chocolate Factory. (Which is another one of my favorite books, even though it’s not going to make it onto this list about algorithms.)

The building blocks of software are algorithms, so here our journey continues after you have established a deep understanding of programming languages.

Modern software is predominantly distributed, and since this book doesn't assume much it is the perfect introduction to algorithm analysis, concurrency, and distributed systems. And the best part is that you can just jump in and build these algorithms yourself.