This repo includes a set of tests that can be used to assess the skills of a candidate for a JavaScript position, or to evaluate and improve one's own skills. It is based on the awesome but outdated js-assessment repo by Rebecca Murphey. The aim of this repo is to challenge engineers to solve a challenge using different approaches and to keep the solutions updated with changes in the javascript language.
To use the tests, you will need to install Node.
You can clone or download this repo. Once you have done so, from the root directory of the repo, run:
yarn test
You can then view the tests in your browser at http://localhost:51204/vitest/.
When you visit that page, all of the tests should be failing; your job is to
get the tests to pass. To do this, you'll need to refer to the tests in the
files in the tests directory, and edit the files in the code directory.
Once you update a test, the page in the browser will automatically reload where you can see
whether it worked.
You can also run the tests on the command line:
yarn test:cli
Submit a pull request! The tests are currently loosely organized by topic, so
you should do your best to add tests to the appropriate file in the tests directory, or
create a new file there if you don't see an appropriate one.
If you're not sure how or where to add a test, please open an issue.
If your tests need data that can be fetched via XHR, stick a .json file in
the data directory; you can access it at /data/<filename>.json.
First, bear in mind that looking up the answers is going to teach you a whole
lot less than you'll learn by working on the tests, even if you occasionally get
stuck. I'd recommend only looking at the answers once you have the tests
passing, to see if there's another way you could have approached the
problem. When you're ready to look at the answers, you can find them in the solutions
branch. I'll do my best to keep them up to date.
This repo uses the Vitest test framework.
If you have any suggesting to improve this repo, check out the issues for details, pull requests welcome!
Copyright © 2023 Chris Seckler with many thanks to several contributors.
This work is licensed under a MIT License.