The most recommended computer science books

Imagine sitting in a room with 50 of the top software architects in the world and have each of them tell you some brief words of advice about being a software architect.

Welcome to “97 Things Every Software Architect Should Know”. Each 2-page spread features a top software architect offering their advice on some aspect of software architecture. From technical skills to soft skills, this book has it all.

This book is a must-read if you are a software architect, or even thinking about becoming one.

This book is an extremely rigorous and formal presentation of Game Theory concepts to Ph.D. students.

The chapters about complete information games and repeated games are particularly superb relative to other advanced books in this field. It also offers chapters on cooperative games, which is quite uncommon in other books (both at the undergraduate and graduate levels.)

The coverage of signaling games, Perfect Bayesian Equilibrium, and equilibrium refinements is relatively brief compared to most other topics in the book, but the book is still great.

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.

Continuing down the engineering part of this mini-curriculum, we have a collection of interesting ideas, each written by a different author, all of them inspiring.

Some of the chapters in this book I have reread more times than I can count, because the ideas are so original and intriguing that my fingers start to tingle.

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.

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. 

One of the most treasured and unusual books in my personal library. It’s an encyclopedia from another world, entirely written in a made-up language. Page after page of haunting and strange illustrations, organized into specific categories and concepts. Sitting with this book transports me back to the time before I could read, when words felt like incomprehensible symbols. Taking the time to puzzle over this book feels like such a valuable experience. It takes me right out of the familiar ways of taking in information and puts me in a state of mind that has to search and consider the juxtaposition of images and ideas in totally new ways. I can’t recommend this book enough.

This book provides a brief introduction to the concept of algorithms before discussing the limitations of computation. Specifically, Harel explains undecidable problems (that is, problems for which no algorithm exists) and infeasible problems (that is, problems for which only algorithms are known that have an exponential runtime). I like this book (and its splendid title) because of its focus on the limitations of computation. Harel does a marvelous job in explaining two difficult topics about computation. The understanding of any scientific discipline requires the understanding of its limits, and the limits of computation are as significant as they are surprising.

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.

After more than thirty years of teaching college students, Dr. “Tony” Fredericks put pen to paper to create a practical and solution-based guide for adjunct professors.

First, the reader is guided to establish best teaching practices for this specialized group of students. The author also provides countless tools as he details how to select a textbook and design a syllabus, define first-day teaching expectations, pose effective questions to propel stimulating discussions, and teach diverse populations of students.

Meticulously constructed, the author composes the text in a well-organized and easy-to-read format. As an aside, Dr. Tony Fredericks currently is the author of over one-hundred-seventy books, comprised as adult non-fiction books, children’s books, pre-service teacher books, and teacher resource books. Not too shabby.