# Automation

Terms defined: DevOps, JavaScript Object Notation, build manager, continuous integration, critical mass, linter, package manifest, pattern rule, post-commit hook, pre-commit hook, static analysis, style checker

Everyone is talking about DevOps these days, even though (or perhaps because) no one can quite agree what it is. The term mostly seems to refer to practices that minimize the time between a developer implementing a change and that change being tested, integrated, tested again, and deployed. Those practices have one thing in common: automating as many steps as possible to make them fast and reliable. You may not be required to do this for your project, but if you have time, you should try to do a little—it will save time when you are up against the end-of-term deadline, and more importantly, prevent mistakes when you are stretched thin.

## Build Manager

The foundation for almost all automation in software development is a build manager—a tool that will transform what you've typed into what you want to deliver. The origin build manager is Make, which was invented in 1975 by a summer intern at Bell Labs to compile programs in which some modules depended on others. To use it, you create a Makefile that specifies the dependencies between the files in your project and the commands needed to update them. For example:

game.exe : game.bc graphics.bc utils.bc
tx -E -o game.exe game.bc graphics.bc utils.bc

%.bc : %.grace
tx -C $<  tells Make that game.exe can't be built until game.bc, graphics.bc, and utils.bc exist, and that once they do, the way to create game.exe is to run the tx compiler with several options. Below that is a pattern rule telling Make how to create any .bc file from a .grace file with the same root name; the cryptic expression $< is Make's way of saying "the first thing the target depends on".

Make has been used by hundreds of thousands of programmers for more than thirty years, but has some fundamental flaws. The first is its syntax, which looks like something produced by a cat dancing on the keyboard. The second is that it runs commands by handing them over to whatever operating system it is running on, which make portability a constant headache. (Quick, should you use rm or del to delete a file?) Third, Make doesn't have a debugger: the only way to track down problems in your build configuration is to stare at the configuration file until little drops of blood form on your forehead.

I could live with ugly syntax—if Ie kan lurn Inglish speling, Ie kan lurn eneething. But the lack of a debugger is a never-ending headache, because real build systems aren't just configured: they're programmed. For example, this book's Makefile checks the consistency of cross-references and glossary entries, makes sure all the bibliography citations are in place, and copies files to my web site, and is more complex than many programs I've written. Thinking of it as a "configuration" file is a mistake: you have to approach builds as a programming problem.

The current generation of build managers dispense with custom configuration file syntax, but most still don't have debuggers. The package.json file used by Node.js serves as both a package manifest and a build file—as the example below shows, some of its entries describe the package or its dependencies, while others store commands that can be re-run by typing things like npm run test:

{
"name": "stjs",
"version": "1.0.0",
"description": "Software Tools in JavaScript",
"type": "module",
"main": "index.js",
"scripts": {
"ejslint": "ejslint inc/*.html *.md */*.md",
"serve": "http-server docs -p 4000 --utc",
"test": "mocha */test/test-*.js"
},
"dependencies": {
"argparse": "^2.0.1",
"caller": "^1.0.1",
"csv": "^5.3.2",
..
}
}


package.json files have two flaws: there is no standard way to write comments (since JSON itself doesn't have this) and there is no way to express dependencies between tasks, i.e., there's no way to say, "A depends on B which depends on C".

Snakemake and Rake take the idea of "build file as data structure" one step further. Their users describe dependencies as small Python or Ruby programs respectively, making use of an extensive support library that handles dependencies, invokes appropriate compilers, and so on. Debugging is still problematic, but at least it's possible. Unfortunately, like front-end JavaScript frameworks and static site generators, a simple build tool is so simple to create that hundreds have proliferated. As a result, none has achieved critical mass.

Whatever you choose or are told to use, please follow these rules:

Pick something that plays nicely with your other tools.
For example, most Java editors and IDEs integrate with a build tool called Ant, which means they can jump directly to compilation errors when they occur.
"Reduce, re-use, recycle" is as important for software as it is for daily life, but every library you depend on is one more way for your project to accumulate technical debt. Recent research shows that we are all biased toward solving problems by adding things instead of taking them away Meyvis2021; checking the packages your project depends on before every release and cutting any you can will prevent a lot of future headaches.
Always use the build manager—never compile or copy things by hand.
This isn't just for efficiency's sake: if any of the things you need to do to get your application up on your web site have to be done by hand, the odds are that you'll forget a crucial step right before your end-of-term demo.
Always use the build manager—never compile or copy things by hand.
Yes, I'm repeating myself, but this time the reason is different. If you do something by hand, one of your teammates might do it differently. "But it works on my machine!" isn't something you want to hear an hour before a deadline…

A good way to start using a build manager is to create a "version zero" of the project. Set up the build and make sure it works even when there isn't anything to compile, run, test, or copy. Now add something—anything. Does the build still work? If it does, you're on your way.

### Never break the build

Once you have a build system in place, never commit anything to version control that breaks the build. This is one of the golden rules of working in a team: if your code won't compile, or doesn't pass whatever automated tests you have, then putting it into the repository means putting every other person on your team into exactly the same broken state you're in. When you're working on your own, it's OK to use version control as a way to transfer files from one machine to another, or as a way to back things up at the end of the day. Do not carry this habit over to teamwork.

## Checking Style

One task you should add to your build system right at the start of the project is something that runs a style checker to make sure your code follows the team's formatting rules. (Style checkers are often called linters because an early one called lint looked for problems in C programs.) Some of these rules are as simple as "no method can be longer than 100 lines" or "class names must be written in CamelCase". Modern tools like ESLint for JavaScript, Checkstyle for Java, or Black for Python can do a lot more: they can find code that is never called, parameters that are never used, duplicated code that could be refactored, and a lot more. Code reviews are much more straightforward when the code you're looking at is guaranteed to be clean, so if something violates style rules, treat it as a broken build.

Style checkers are just one kind of static analysis tool, since they work by parsing the source code for your program rather than by watching the program run. Compilers also do a lot of static analysis; the non-fatal warnings they produce are a lot more useful than many students realize, and a "zero warnings" policy can prevent a lot of subtle bugs. As we'll see in , requiring type definitions in code helps programmers understand software as well.

## Continuous Integration

Build tools will do a lot more for you if you adopt some kind of continuous integration system such as Travis CI or GitHub Actions. These can be set up to run either at regular intervals (e.g., every hour or at three a.m.), or every time someone checks into version control (which I find more useful). Each time they run, they check a fresh copy of the project out of version control, build it, re-run all the tests, and post the results to the project's blog, web site, and mailing list.

Research has proven the benefits of CI Hilton2016. It acts as a "heartbeat" for the project: as soon as anything goes wrong, everyone knows. It also encourages good development practices: if someone checks something in that doesn't compile, run, or pass the project's tests, everyone will know very quickly. (Funnily enough, after the system has shamed you a couple of times, you'll stop checking in broken code…)

For example, we can check every attempt to push changes to the repository for a Python project, and every pull request created for that repository, by putting these commands in a file called .github/workflows/check.yml:

name: Check

on: [push, pull_request]

jobs:
check:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v2

- name: Setup Python
uses: actions/setup-python@v1
with:
python-version: 3.9

- name: Install dependencies
run: |
pip install -r requirements.txt

- run: black --check .
- run: flake8
- run: pytest


From top to bottom:

• The name key tells GitHub what this action is called, while the values associated with the on key determine when the action runs.

• An action can have many jobs (or tasks); in this case there's just one called check. We want it to run on the latest version of Ubuntu Linux.

• The uses key tells GitHub to run the steps in another action before running the steps for this one; actions/checkout@v2 points at steps in GitHub's own actions repository, but there are lots of others.

• Similarly, we can use a pre-defined action to set up Python 3.9, and then use pip to install our project's requirements (which are listed in a file called requirements.txt). This ensures that we have a brand-new environment every time we run our checks.

• We can now run our checks: black to check code style, flake8 to look for common errors, and pytest to run our tests. If any of these fail (i.e., if any return a non-zero exit status), the overall action fails and the push or pull request doesn't go through.

Configuring actions like these is a programming task like any other, except for the fact that you specify what you want in YAML rather than in Python, JavaScript, or some other language. Zampetti2020 looks at how not to use CI, and can serve as a good checklist of things to avoid.

If you don't want to go this far, you can add pre-commit or post-commit hooks to your repository to specify actions to run on your machine before and after each commit. When I set these up, I almost always have them run commands via the build manager so that I can also run checks whenever I want.

### Getting past the dip

Any new tool or practice initially makes you less productive, so if you're up against a deadline (as you almost always will be), the safest course of action is often to keep doing things the "wrong" way because there isn't time to learn how to do it more efficiently. This is why I think that lab exams should be part of project courses, i.e., that you should be required to demonstrate to your instructor that you're able to use a build manager or a debugger. People learn how to use version control because they're required to in order to submit work for grading; if you are required to submit a screen recording of you using particular tools as part of an assignment, it will help you in the long run.