I’ve spent most of my life writing code—and too much of that life teaching new programmers how to write code like a professional. If it’s true that you only truly understand something after teaching it to someone else, then at this point I must really understand programming! Unfortunately, that understanding has not led to an endless stream of bug-free code, but it has led to some informed opinions on programming and books about programming.
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.
I have been working with computers for decades now – having started with programmable handheld calculators and working my way up and down through mainframes, mini- and micro-computers. I always thought there is an art to writing software, and that good software can be read and admired. Maintainability, readability, and testability are some core needs for software, and after going through many programming paradigms, I feel that functional programming (FP) is the way to go – and several modern web frameworks agree. JavaScript (and now, TypeScript) are essential to web development, and I wanted to show how FP could be successfully used with those languages, and thus my book.
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.
Check out the boxed set that brings together Volumes 1 - 4B in one elegant case.
The Art of Computer Programming, Volumes 1-4B Boxed Set
ISBN: 9780137935109
Art of Computer Programming, Volume 1, Fascicle 1, The: MMIX -- A RISC Computer for the New Millennium
This multivolume work on the analysis of algorithms has long been recognized as the definitive description of classical computer science. The three complete volumes published to date already comprise a unique and invaluable resource in programming theory and practice. Countless readers have spoken about the profound personal influence of Knuth's writings. Scientists have marveled at…
I was a humanistic psychotherapist first and came to astrology later and loved the way it didn’t pathologize and gave insight into our character and how that affects our destiny. I started to gather the charts of my psychotherapy clients (with their permission of course) and while not using this in their sessions, I was inspired by how they spoke their charts. Much of my understanding of how planetary positions and aspects manifest has been discovered by listening. I love how aspect patterns repeat through the generations within a family and what ramifications this has on the individuals. Who’s carrying the families karma?
This is another of my books held together with Sellotape.
A T-square is a particularly challenging aspect pattern within a natal chart and Tracy gives vivid descriptions of a variety of possible manifestations. This book will help us to see the positive and the negative outcomes available to us and potentially take more responsibility for the circumstances that befall us.
I love to expand my knowledge and learn not just about new technologies, but how things work. I find it fascinating to dig deep into computer programming, technology concepts, and really geek out on things. That’s why I love software development or programming books that aren’t just about some technology and how to do something, but rather books that really make you think and teach you not just programming skills but critical thinking about problem-solving skills. As a software developer for over 15 years and a person who teaches software developers, I have learned that if someone isn’t entertained, they aren’t learning. That’s why I put together a list of fun, entertaining and useful books.
Wow! This book is exactly what every programmer has always wanted to know or even felt guilty about not knowing and it’s all presented in an extremely simplified and fun way.
This is one of those books where you get excited in the morning when you wake up because you know you are going to be able to read more in the book and you are hoping the book will never end.
It’s rare to find a big book that I enjoyed reading so much and felt so short. This book covers almost everything you ever wondered about computer science. After reading this book, I felt like I finally understood everything a programmer was supposed to know and I no longer felt that nagging feeling of being an imposter.
My life has been about programming for as long as I can remember. Learning to code was a way to connect with my dad and express my creativity at a young age. Since I grew up with code, it became the way I understood the world; often I could look at a process or program and immediately see its source code in my mind. I developed a very strong sense of aesthetics searching for “perfect code,” which for me was code that was not only error-free but resistant to errors. My studies, research, and career is about moving myself and all programmers closer to that goal: Software that never fails.
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.
How do the experts solve difficult problems in software development? In this unique and insightful book, leading computer scientists offer case studies that reveal how they found unusual, carefully designed solutions to high-profile projects. You will be able to look over the shoulder of major coding and design experts to see problems through their eyes. This is not simply another design patterns book, or another software engineering treatise on the right and wrong way to do things. The authors think aloud as they work through their project's architecture, the tradeoffs made in its construction, and when it was important to…
I love pulling back the curtain on how computers work. I want to go from thinking "that's magic" to "that's unbelievably clever but now I understand how it works." Each time I am able to do this feels like a hard-won but therefore meaningful step toward understanding. I want others to experience this empowering shift. I have a PhD in computer science education, and I want to know what helps people learn. More importantly, I want to know how we can use such discoveries to write more effective books. The books I appreciate most are those that demonstrate not only mastery of the subject matter but also mastery of teaching.
I’ve probably spent more time with this book than with any other technical book. It’s one of those books where you can get as much out of it as you like by revisiting the material at increasing levels of depth. I appreciate the conversational but rigorous tone, the solved examples, the false starts, the intuition that the authors build, and the applications of algorithm design to realistic problems. The Maximum Flow chapter is not to be missed.
Algorithm Design introduces algorithms by looking at the real-world problems that motivate them. The book teaches students a range of design and analysis techniques for problems that arise in computing applications. The text encourages an understanding of the algorithm design process and an appreciation of the role of algorithms in the broader field of computer science. August 6, 2009 Author, Jon Kleinberg, was recently cited in the New York Times for his statistical analysis research in the Internet age.
As a child of the microcomputer revolution in the late 1970s, I’ve always been fascinated by the concept of a general-purpose machine that I could control. The deep learning revolution of 2010 or so, followed most recently by the advent of large language models like ChatGPT, has completely altered the landscape. It is now difficult to interpret the behavior of these systems in a way that doesn’t argue for intelligence of some kind. I’m passionate about AI because, decades after the initial heady claims made in the 1950s, AI has reached a point where the lofty promise is genuinely beginning to be kept. And we’re just getting started.
Alan Turing’s 1936 paper “On Computable Numbers, with an Application to the Entscheidungsproblem” was foundational to the development of computer science. To this day, Turing machines, the theoretical computational devices imagined in Turing’s paper, are a research cornerstone as they embody the concept of “computable.” If a programming language can implement a Turing machine, then the language is deemed Turing complete and is, therefore, general-purpose enough to implement any algorithm.
Turing’s paper is readable, but Petzold’s book breaks it down in minute detail to explain the nomenclature and meaning behind Turing’s words. I believe all computer science students should study this paper, and you’ll be hard-pressed to find a more thorough review than the one presented in this book.
Programming Legend Charles Petzold unlocks the secrets of the extraordinary and prescient 1936 paper by Alan M. Turing
Mathematician Alan Turing invented an imaginary computer known as the Turing Machine; in an age before computers, he explored the concept of what it meant to be computable, creating the field of computability theory in the process, a foundation of present-day computer programming.
The book expands Turing's original 36-page paper with additional background chapters and extensive annotations; the author elaborates on and clarifies many of Turing's statements, making the original difficult-to-read document accessible to present day programmers, computer science majors, math geeks,…
I started programming in high school and wrote software in many domains for 30 years, from the early ARPA-net to massive credit card software. I wrote a FORTRAN compiler with one assistant in a year. I got hassled to do proper project management. Nightmare. It was all about inflated expectations instead of moving fast and winning. Then in 25 years of venture capital investing, I learned from many young companies how the little startups built quickly and well things that giants like Google literally could not get done. This book and my others spell out what I learned from the little guys who beat the giants.
Attending Harvard College gave me the opportunity to collaborate with great programmers in creating the early ARPA-net. But the best course I took was on compiler theory and construction, using an early draft of the material in this book.
Of course I learned how to build a compiler, which I did as my first job after graduating. But more important, I learned that a well-built compiler is a small amount of language-independent code with two major parts.
First the input part that realizes the content of the lexical and grammatical metadata, like today’s LEX and YACC, to turn the program being compiled into a semantic model.
Second the code generator that reads the semantic model and, based on generative model metadata, turns the semantics of the program being compiled to whatever form you want, whether executable code, assembler language, byte code or whatever.
This approach, while indispensable for compilers and…
My life has been about programming for as long as I can remember. Learning to code was a way to connect with my dad and express my creativity at a young age. Since I grew up with code, it became the way I understood the world; often I could look at a process or program and immediately see its source code in my mind. I developed a very strong sense of aesthetics searching for “perfect code,” which for me was code that was not only error-free but resistant to errors. My studies, research, and career is about moving myself and all programmers closer to that goal: Software that never fails.
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.
The new edition of a guide to distributed algorithms that emphasizes examples and exercises rather than the intricacies of mathematical models.
This book offers students and researchers a guide to distributed algorithms that emphasizes examples and exercises rather than the intricacies of mathematical models. It avoids mathematical argumentation, often a stumbling block for students, teaching algorithmic thought rather than proofs and logic. This approach allows the student to learn a large number of algorithms within a relatively short span of time. Algorithms are explained through brief, informal descriptions, illuminating examples, and practical exercises. The examples and exercises allow readers to…
I’ve been a software architect for a very long time. I love hard problems, and I’m very passionate about collaborating with others to find the right solution to them. Software architecture is a challenging, multi-faceted discipline with very few resources to help you make the right decisions. That’s why I’m recommending these books on software architecture. These books helped me become a more effective software architect, and I hope they can help you become more effective as well.
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.
