Fans pick 70 books like Dynamics of Software Development

In my consulting gigs, I come across plenty of clueless remarks. Here's a classic one: “We're falling behind schedule, so let's hire more coders.” Or a more recent gem: “We'll be ten times more productive if we generate code with AI.”

When I encounter such nonsense, I don't facepalm or cringe. Instead, I put on my poker face and drop a quote from The Mythical Man-Month.

In an industry where last year’s book is already outdated, Fred Brooks' collection of essays has been a guiding light for nearly half a century. His aphorisms have become legendary. “The bearing of a child takes nine months, no matter how many women are assigned.” “Adding manpower to a late software project makes it later.” “There is no silver bullet.” The list goes on and on.

John Carmack, one of the greatest programmers of our times, used to revisit this book every year or… show more.

This book’s title is absolutely perfect! There’s no agenda here other than identifying things that will make you a more effective and productive programmer.

That leads to a book packed with solid advice, whether it’s about how to write code or how to think about your career. The authors are consultants, so there are plenty of clear and interesting examples drawn from many different problem domains. That’s super fun for someone like me who’s hyper-focused on a single kind of programming.

Accelerate is a book about data. The authors used data collected during their PhD projects in order to prove The DevOps is effective.

They have all sorts of different ways to measure DevOps, it sufficiency, and the fact that way more projects succeed when you do DevOps, rather than waterfall methodology.

The book essentially show can be used as evidence of return on investment when modernizing your IT department. I am a person who loves data, and thus I absolutely love this book. Also, if you listen to the audiobook version, one of the authors reads it to you and her personality really shines through in a fun way.

I really enjoyed listening to Nicole read a book about to me about data!

This book resonated with me because of its brilliantly simple yet profound idea: care personally and challenge directly. This approach cuts through the surprisingly indirect and impersonal culture often found in Silicon Valley, despite what the media publicizes.

I also loved the many stories involving tech heavyweights Kim had worked with, which added a layer of real-world insight and credibility to her advice. The book made me rethink how authentic communication can transform relationships and drive success in any team.

One way to craft lessons learned is in the form of recommended best practices (or, as I prefer, “good practices”). Best practices represent collected and distilled wisdom from many observers, many projects, and many years of experience. Rapid Development includes 27 best practices for software development, with one chapter devoted to each. Although the book was published more than 25 years ago, most of these are still relevant. Indeed, several of them have been incorporated into routine contemporary practices: evolutionary delivery, designing for change, timebox development, and requirements scrubbing. Techniques such as inspections, miniature milestones, principled negotiation, and reuse are perennially pertinent.

Many of the most significant principles of effective software development are timeless. They’re independent of the development life cycle or model, programming language, application type, and so forth. Although this book is quite a few years old now, nearly all of its contents are still valid. The 201 principles cover the full spectrum of software engineering: general principles, requirements engineering, design, coding, testing, management, product assurance, and evolution. The descriptions of each principle are concise, whereas my 60 lessons in Software Development Pearls go into a great deal more detail and offer many practical techniques.

There’s an unfortunate tendency among young software people to disregard knowledge from the past as irrelevant to them. That’s not correct. This book can help close significant gaps in any practicing software developer’s knowledge.

This book helped me set my initial approach to software development and I still periodically return to it for grounding.

An MIT project theorized that new-fangled PC software developers knew something mainframe and mini-computer makers didn’t. MIT’s research revealed something else entirely: Microsoft had uniquely effective ideas on how to build complex products in rapidly evolving competitive markets. Here is “agile” before it was put into the Manifesto in 2001, in a more complete form. Ever wonder where the idea of a team comprising functional specialists with overlapping roles, united by a common goal, came from? Or incremental feature evolution with periodic synchronization and constant testing? Early brilliance still of foundational relevance, in a coherent and engaging form.

Many agile projects employ user stories as a way to represent requirements rather than a more traditional approach combining use cases and functional requirements. I favor the latter approach for several reasons. Nonetheless, user stories are well established in the agile development world, and if you wish to learn about them, there’s no better author to read than Mike Cohn. Cohn describes how to craft user stories well and how they fit into the agile development process.

“Good agile testing is good context-driven testing applied in an agile context.”

The authors of this book summarize their decades of experience in software testing in over 100 lessons they learned. Follow them along different aspects of the tester’s job, as they re-tell various stories collected over the years with some clear guidance to surviving and testing project.

These software testing industry leaders have some timely contextual advice in here – whether you work as a tester on an agile team or in a more traditional fashion.

A thoroughly fascinating (and fascinatingly thorough) look at engineering practices at Google.

It’s an encyclopedia written by a bunch of authors, so some of the chapters are a little dry, but for those of us who aren’t on teams with 25,000 engineers it’s spell-binding to see what programming at that sort of scale looks like. Some of the chapters prompted us to think really hard about the way we do things at Sucker Punch.