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This page discusses what build systems are, what they do, why you should use a build system, and why compilers and build scripts aren‘t the best choice as your organization starts to scale. It’s intended for developers who don't have much experience with a build system.
Fundamentally, all build systems have a straightforward purpose: they transform the source code written by engineers into executable binaries that can be read by machines. Build systems aren‘t just for human-authored code; they also allow machines to create builds automatically, whether for testing or for releases to production. In an organization with thousands of engineers, it’s common that most builds are triggered automatically rather than directly by engineers.
The need for a build system might not be immediately obvious. Most engineers don't use a build system while learning to code: most start by invoking tools like gcc or javac directly from the command line, or the equivalent in an integrated development environment (IDE). As long as all the source code is in the same directory, a command like this works fine:
javac *.java
This instructs the Java compiler to take every Java source file in the current directory and turn it into a binary class file. In the simplest case, this is all you need.
However, as soon as code expands, the complications begin. javac is smart enough to look in subdirectories of the current directory to find code to import. But it has no way of finding code stored in other parts of the filesystem (perhaps a library shared by several projects). It also only knows how to build Java code. Large systems often involve different pieces written in a variety of programming languages with webs of dependencies among those pieces, meaning no compiler for a single language can possibly build the entire system.
Once you're dealing with code from multiple languages or multiple compilation units, building code is no longer a one-step process. Now you must evaluate what your code depends on and build those pieces in the proper order, possibly using a different set of tools for each piece. If any dependencies change, you must repeat this process to avoid depending on stale binaries. For a codebase of even moderate size, this process quickly becomes tedious and error-prone.
The compiler also doesn’t know anything about how to handle external dependencies, such as third-party JAR files in Java. Without a build system, you could manage this by downloading the dependency from the internet, sticking it in a lib folder on the hard drive, and configuring the compiler to read libraries from that directory. Over time, it's difficult to maintain the updates, versions, and source of these external dependencies.
Suppose that your hobby project starts out simple enough that you can build it using just a compiler, but you begin running into some of the problems described previously. Maybe you still don’t think you need a build system and can automate away the tedious parts using some simple shell scripts that take care of building things in the correct order. This helps out for a while, but pretty soon you start running into even more problems:
It becomes tedious. As your system grows more complex, you begin spending almost as much time working on your build scripts as on real code. Debugging shell scripts is painful, with more and more hacks being layered on top of one another.
It’s slow. To make sure you weren’t accidentally relying on stale libraries, you have your build script build every dependency in order every time you run it. You think about adding some logic to detect which parts need to be rebuilt, but that sounds awfully complex and error prone for a script. Or you think about specifying which parts need to be rebuilt each time, but then you’re back to square one.
Good news: it’s time for a release! Better go figure out all the arguments you need to pass to the jar command to make your final build. And remember how to upload it and push it out to the central repository. And build and push the documentation updates, and send out a notification to users. Hmm, maybe this calls for another script...
Disaster! Your hard drive crashes, and now you need to recreate your entire system. You were smart enough to keep all of your source files in version control, but what about those libraries you downloaded? Can you find them all again and make sure they were the same version as when you first downloaded them? Your scripts probably depended on particular tools being installed in particular places—can you restore that same environment so that the scripts work again? What about all those environment variables you set a long time ago to get the compiler working just right and then forgot about?
Despite the problems, your project is successful enough that you’re able to begin hiring more engineers. Now you realize that it doesn’t take a disaster for the previous problems to arise—you need to go through the same painful bootstrapping process every time a new developer joins your team. And despite your best efforts, there are still small differences in each person’s system. Frequently, what works on one person’s machine doesn’t work on another’s, and each time it takes a few hours of debugging tool paths or library versions to figure out where the difference is.
You decide that you need to automate your build system. In theory, this is as simple as getting a new computer and setting it up to run your build script every night using cron. You still need to go through the painful setup process, but now you don’t have the benefit of a human brain being able to detect and resolve minor problems. Now, every morning when you get in, you see that last night’s build failed because yesterday a developer made a change that worked on their system but didn’t work on the automated build system. Each time it’s a simple fix, but it happens so often that you end up spending a lot of time each day discovering and applying these simple fixes.
Builds become slower and slower as the project grows. One day, while waiting for a build to complete, you gaze mournfully at the idle desktop of your coworker, who is on vacation, and wish there were a way to take advantage of all that wasted computational power.
You’ve run into a classic problem of scale. For a single developer working on at most a couple hundred lines of code for at most a week or two (which might have been the entire experience thus far of a junior developer who just graduated university), a compiler is all you need. Scripts can maybe take you a little bit farther. But as soon as you need to coordinate across multiple developers and their machines, even a perfect build script isn’t enough because it becomes very difficult to account for the minor differences in those machines. At this point, this simple approach breaks down and it’s time to invest in a real build system.