Fans pick 100 books like A Discipline 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 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.

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.

This popular book takes a broad perspective that surveys the main physical and logical layers from which all digital devices are made.

I like the accessible writing style, aimed at lay readers, and the book’s companion website, where one can experiment interactively with many of the artifacts described in the book. The second edition includes a new section that focuses on a functional subset of Intel 8080, the microprocessor that ushered the personal computing revolution, and the instruction set used by many PCs and servers today.

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.

The fields of Psychology, Economics, and Biology are well-known for offering interesting and informative introductory courses that provide a doorway into the area for budding scientists but also essential background knowledge appropriate for any educated person.

In Computer Science, we don't really do things that way. I wanted to offer a new kind of Computer Science introductory course that laid out the coolest ideas we have to offer along with compelling descriptions of why they matter.

I ended up using this book as the required reading in the class I built because it tells a personal, moving story while taking the reader from the nuts and bolts of bits and bytes all the way up to cutting-edge ideas surrounding artificial intelligence. It's a great read! Plus, it's short so I thought I could get my students to actually finish it.

This book was written in the late 60s, when everything was breaking loose from traditional values, including writing styles. Brunner did a very good job of anticipating how technology and changing social norms would change the world in the not-so-distant future.

It's all there: sexual freedom, legal drugs, religion, computers, crazy mass killers called muckers, corporate empires, a 7 billion population, global events, and the personalized internet.

I like the way the story was written, a new wave pop art style intermixed with traditional passages blaring out a series of seemingly unrelated events that are strung together by a group of unrelated characters who carry the complex story through to a surprising ending.

Before I read this book, I knew a bunch of facts about the different pieces of computer systems. After I read it, I understood how those pieces fit together. Building all those pieces myself, starting from the simplest logic gates and working my way up, made some fundamental concepts finally click—like how a processor decodes an instruction.

I especially loved the book’s hands-on structure: each chapter is a project where you get a specification and test suite for the component you need to build, but you have to figure out exactly how to build it for yourself. Completing the projects often felt like solving a fun puzzle, and it made the concepts stick in a way that just reading about them wouldn’t have.

This weighty tome delves deep into the low-level working of computer programs.

This book is a great resource for professional programmers who work close to the machine in such fields as embedded software, cybersecurity, and device drivers. Assuming a basic knowledge of the C language, Bryant and O’Hallaron, two CMU professors, teach how to read and understand compiled code, how to optimize it for better performance, and how to avoid common pitfalls.

This is a hard-core technical book, written by engineers for engineers, in a dense style that is nonetheless accessible and practical. I like the numerous applied problems, each accompanied by a worked-out solution.