Details:
1. All tests now live in `test`. All test dependencies that aren't from npm live
in `test-deps`.
2. The QUnit tests are gone, as well as their dependencies. Half of them
duplicated existing tests, and some of them depended on the real DOM to
properly test.
3. All tests are now using Mocha to run the tests, Chai for assertions, and
Sinon and Sinon Chai for testing some callbacks.
4. Tests are run through mocha-phantomjs. If you want to run just the tests,
run `grunt mocha_phantomjs` or fire up a server in the root and open
`http://localhost:<port>/test/index.html`, e.g. `python3 -m http.server`.
5. The linter I chose is ESLint. It is relatively easy to configure, but with a
lot of flexibility. The rules I chose mostly were in tune to the style the
project was already using. I'm not including a style guide in this commit,
but one will likely come. You can check out the `.eslintrc` in the root and
in `test/` for the two configs. The `.eslintignore` includes a TODO for
`mithril.js` itself targeted at me, in the root.
Other info:
- As a drive-by fix, I fixed line endings on a few of the files.
- I also took care of a few other files and linted them as I went:
- `Gruntfile.js`
- `test/input-cursor.html` (was in `tests/`)
- `test/svg.html` (was in `tests/`)
- `docs/layout/tools/template-converter.html`
- `docs/layout/tools/template-converter.js`
I didn't test the template converter after linting it, because it needs
further scrutiny to ensure it works with the latest version of Mithril. I
know the API has changed a little, which is why I want to be sure.
- I simplified the `.travis.yml` file because none of the tests are run directly
through Node anymore. They are always run in a browser of some kind.
Hopefully, this turned out all right...
This is in preparation for a PR, to reduce potential for merge conflicts
with either my PR or others', since mine will modify a large amount of
the main file.
1. Do some temporary style modifications to help make the code more readable
for profiling (with help from ESLint).
2. Profile the code, and optimize accordingly.
