If the job fails early (e.g. during linting), the 'cat debug.log' step would *also* fail.
This would confuse GA into thinking that this is the crucial thing and highlights it.
This misleads the user into looking at the wrong thing.
As documented in #5541, there are some Kernel issues that can
sporadically cause the test run to fail. Add continue on error with a
loud comment to let readers know what the issue(s) might be.
Build a new version of Serenity in CI that doesn't have all the debug
symbols on, or we'd be waiting a very long time to boot.
Insert a TestRunner entry into SystemServer.ini that will run a shell
script that runs tests in /bin and /usr/Tests and shuts down the system
in the new self-test boot mode. Also make sure enough basic services are
started in self-test such that the tests will actually run properly.
This will make it easier to keep macos tests and non-mac tests in
lockstep. Also, make sure flake8 and python are installed. This also
makes it easier to add other OS targets if we want.
* Add SERENITY_ARCH option to CMake for selecting the target toolchain
* Port all build scripts but continue to use i686
* Update GitHub Actions cache to include BuildIt.sh
A good number of contributors use macOS. However, we have a bit of
a tendency of breaking the macOS build without realising it.
Luckily, GitHub Actions does actually supply macOS environments,
so let's use it.
CMake tests usually takes ~40 seconds. However, sometimes it deadlocks
and is only timed out after the 6 hour time limit.
Let's set a 2 minute timeout to make it fail sooner. 2 minutes instead
of 1 for good measure.
There are cases where Lagom will build with GCC but not Clang.
This often goes unnoticed for a while as we don't often build with
Clang.
However, this is now important to test in CI because of the
OSS-Fuzz integration.
Note that this only tests the build, it does not run any tests.
Note that it also only builds LagomCore, Lagom and the fuzzers.
It does not build the other programs that use Lagom.
CodeQL is a static analysis technology that was purchased by GitHub
and has been tightly integrated into the platform. It's different
from most other static analysis solutions because it's based on a
database built from your codebase, and then language specific rules
can be executed against that database. The rules are fully user
extensible, and are written in a datalog/query language.
The default cpp language rules coming from CodeQL will probably find
some issues, the ability to easily write custom rules/queries will
lend it self nicely to allowing us to validate Serenity specific
semantics are followed throughout the code.
References:
- https://www.youtube.com/watch?v=AMzGorD28Ks
- https://securitylab.github.com/tools/codeql
