Extreme Programming Explained by Kent Beck (Addison-Wesley 2000). I love this book. Yes, I tend to take a radical approach to things but I've always felt that there could be a much different, much better program development process, and I think XP comes pretty darn close. The only book that has had a similar impact on me was PeopleWare (described below), which talks primarily about the environment and dealing with corporate culture. Extreme Programming Explained talks about programming, and turns most things, even recent “findings,” on their ear. They even go so far as to say that pictures are OK as long as you don’t spend too much time on them and are willing to throw them away. (You’ll notice that this book does not have the “UML stamp of approval” on its cover.) I could see deciding whether to work for a company based solely on whether they used XP. Small book, small chapters, effortless to read, exciting to think about. You start imagining yourself working in such an atmosphere and it brings visions of a whole new world.

UML Distilled by Martin Fowler (2^nd edition, Addison-Wesley, 2000). When you first encounter UML, it is daunting because there are so many diagrams and details. According to Fowler, most of this stuff is unnecessary so he cuts through to the essentials. For most projects, you only need to know a few diagramming tools, and Fowler’s goal is to come up with a good design rather than worry about all the artifacts of getting there. A nice, thin, readable book; the first one you should get if you need to understand UML.

The Unified Software Development Process by Ivar Jacobsen, Grady Booch, and James Rumbaugh (Addison-Wesley 1999). I went in fully prepared to dislike this book. It seemed to have all the makings of a boring college text. I was pleasantly surprised – only pockets of the book contain explanations that seem as if those concepts aren’t clear to the authors. The bulk of the book is not only clear, but enjoyable. And best of all, the process makes a lot of practical sense. It’s not Extreme Programming (and does not have their clarity about testing) but it’s also part of the UML juggernaut – even if you can’t get XP adopted, most people have climbed aboard the “UML is good” bandwagon (regardless of their actual level of experience with it) and so you can probably get it adopted. I think this book should be the flagship of UML, and the one you can read after Fowler’s UML Distilled when you want more detail.

Before you choose any method, it’s helpful to gain perspective from those who are not trying to sell one. It’s easy to adopt a method without really understanding what you want out of it or what it will do for you. Others are using it, which seems a compelling reason. However, humans have a strange little psychological quirk: If they want to believe something will solve their problems, they’ll try it. (This is experimentation, which is good.) But if it doesn’t solve their problems, they may redouble their efforts and begin to announce loudly what a great thing they’ve discovered. (This is denial, which is not good.) The assumption here may be that if you can get other people in the same boat, you won’t be lonely, even if it’s going nowhere (or sinking).

This is not to suggest that all methodologies go nowhere, but that you should be armed to the teeth with mental tools that help you stay in experimentation mode (“It’s not working; let’s try something else”) and out of denial mode (“No, that’s not really a problem. Everything’s wonderful, we don’t need to change”). I think the following books, read before you choose a method, will provide you with these tools.

Software Creativity, by Robert Glass (Prentice-Hall, 1995). This is the best book I’ve seen that discusses perspective on the whole methodology issue. It’s a collection of short essays and papers that Glass has written and sometimes acquired (P.J. Plauger is one contributor), reflecting his many years of thinking and study on the subject. They’re entertaining and only long enough to say what’s necessary; he doesn’t ramble and bore you. He’s not just blowing smoke, either; there are hundreds of references to other papers and studies. All programmers and managers should read this book before wading into the methodology mire.

Software Runaways: Monumental Software Disasters, by Robert Glass (Prentice-Hall 1997). The great thing about this book is that it brings to the forefront what we don’t talk about: how many projects not only fail, but fail spectacularly. I find that most of us still think “That can’t happen to me” (or “That can’t happen again”) and I think this puts us at a disadvantage. By keeping in mind that things can always go wrong, you’re in a much better position to make them go right.

Object Lessons by Tom Love (SIGS Books, 1993). Another good “perspective” book.

Peopleware, by Tom Demarco and Timothy Lister (Dorset House, 2^nd edition 1999). Although they have backgrounds in software development, this book is about projects and teams in general. But the focus is on the people and their needs rather than the technology and its needs. They talk about creating an environment where people will be happy and productive, rather than deciding what rules those people should follow to be adequate components of a machine. This latter attitude, I think, is the biggest contributor to programmers smiling and nodding when XYZ method is adopted and then quietly doing whatever they’ve always done.

Complexity, by M. Mitchell Waldrop (Simon & Schuster, 1992). This chronicles the coming together of a group of scientists from different disciplines in Santa Fe, New Mexico, to discuss real problems that the individual disciplines couldn’t solve (the stock market in economics, the initial formation of life in biology, why people do what they do in sociology, etc.). By crossing physics, economics, chemistry, math, computer science, sociology, and others, a multidisciplinary approach to these problems is developing. But more importantly, a different way of thinking about these ultra-complex problems is emerging: Away from mathematical determinism and the illusion that you can write an equation that predicts all behavior and toward first observing and looking for a pattern and trying to emulate that pattern by any means possible. (The book chronicles, for example, the emergence of genetic algorithms.) This kind of thinking, I believe, is useful as we observe ways to manage more and more complex software projects.