For my first book review, I decided to write about a wonderful book I discovered about a year ago that I think not too many people know about, and that is Working Effectively with Legacy Code (Robert C. Martin Series)
.I got this book in my first week as a Google intern. Since I had some spare time in the evenings and on the weekends I read it right away and found it absolutely amazing. It basically talks about how to deal with the fact of changing requirements. In the early days of OOP, there was a tendency to over-engineer a project (trying to predict every possible change ahead of time, overuse of inheritance etc.). People soon realized that, while proper design is essential, you just can't predict every possible change, and sometimes you'll have to change your design to accommodate the new requirements. This is where the idea of refactoring code comes in. It's a process in which you change your code while preserving behavior, making it "nicer", in an attempt to make the behavior easier to change in a later step.
The main problem here is preserving behavior while changing things. This can lead to all sorts of headaches and problems, but can be made a lot easier if your code has tests. This is also the main premise of this book; the author loosely defines legacy code as code without tests (and also code that's older then three months or so, which is probably a lot shorter than most people would think). There has been some controversy over tests a few months ago in the "blogosphere", mainly in posts and podcasts by Joel Spolsky and Jeff Attwod on one side, and Robert Martin on the other, all of whom are well respected (for good reason) in the community. Basically, Joel and Jeff argue that Test Driven Development is going too far, and test can make your code harder to change (because you have to change your tests as well). While this might be true sometimes, I don't think it's a valid point if you design your test right. You should be testing your APIs and not your implementations (which is certainly not always possible, but should be a goal). Sure, writing a piece of code (a class for example) will take a bit longer initially because you'll need to write tests for it, but you get several benefits from that. First, you write code that uses your class, therefore exposing some possible weak spots in your API. Second, once you're done, you can be reasonably sure that your class does what you want. Also, when it comes time to change the implementation (or the API, which is not too big a deal if it's a small internal API - and someone else might be making the change, or it's been a year since you wrote the initial code), you'll have a safety-net since you'll be able to tell early if you broke something (there might of course be things you miss, but a lot fewer of them). On the other hand, you just can't unit test everything, but that's OK too. You can do some tests manually, or use specialized tools to automate that as much as possible. I feel that unit tests also provide great documentation for what the API is doing and how to use it (still, you should write more formal docs for external APIs :).
One area especially where I think unit tests are extremely important are scripting languages. Many people used to think (or still do) that programs in scripting tend to be harder to change or more prone to "silly" bugs due to typos that don't get detected by the compiler. While this can be somewhat mitigated with using good IDE-s, having solid unit tests will pretty much eliminate these kinds of bugs and you'll be dealing with much the same bugs you were dealing with in compiled languages.
So back to the book... This book will show you a wealth of options for creating this testing safety-net where there isn't any through a series of realistic examples in Java, C++ and C (although most of the techniques presented are applicable to most languages). It starts of by talking about breaking dependencies as the crucial step in getting (parts of) legacy code under tests. BTW, there is a lot of great material on dependency (and dependency injection) and how testing can make your code less coupled in the first place on the Google Testing Blog. Well worth reading and watching the YouTube videos.
Then it introduces fakes and mocks that let you replace complex objects and interactions in your tests with simple ones, thus making tests faster (connecting to a fake database locally, vs. connecting to a database over the network for example), more focused and less flaky (they won't fail if the network fails or the database dies). Then Feathers talks about seams, which are ways to change behavior of some code without editing in that place. He introduces a lot of techniques that range from fairly obscure (like preprocessing and linking seams) to the more common object seams.
In the next third of the book, he discusses how to deal with things like big classes that do a ton of things, how to go about understanding how objects interact in a complicated system and things like that. This part is mostly about creating the right mindset for dealing with legacy code, although most of the techniques presented are quite practical.
Finally, the third part of the book contains the dependency breaking techniques the first two parts have been building up to in a really nice catalog that can be a great reference. You should read this book once from cover to cover to get it, and then skim it a few times in the following year to index the techniques better into your brain (and of course use the book as a reference).
In conclusion, I think this book is definitely worth reading (if not owning). Even if you don't deal with legacy code on a day to day basis (which is probably rare), it will change the way you look at the new code you're writing, and hopefully convince you that you should be writing unit tests. Try it! :) (if you can get someone to review your code as well, you'll sleep even better, but that's another topic :).
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