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Misc #20254

closed

Add Launchable into Ruby CI

Added by ono-max (Naoto Ono) 3 months ago. Updated 3 months ago.

Status:
Closed
[ruby-core:116664]

Description

I’m a software engineer who works at Launchable, Inc.
Some Ruby CI maintainers have granted me (Naoto Ono) the permission to integrate our service, Launchable into ruby/ruby. This decision was made during the meeting.
Thus, I have created the ticket to share the benefit and progress.

Progress

Currently, both ruby/debug and ruby/vscode-rdbg has started using Launchable.

Benefits

By introducing Launchable, we can enjoy the following benefits:

Rich UI to see stderr and stdout in failed tests

Some Ruby developers find it challenging to review test failure logs in Github Actions. Launchable provides a rich UI that makes it easier to examine stderr and stdout related to test failure.

Screenshot 2024-01-29 at 19 23 08

Test reports in Github comments

Identifying which CI job failed in the Github UI can be cumbersome. Launchable addresses this by creating a comment that summarizes test results directly in Github pull request.
This enhancement will significantly improve the development experiment.

Test reports in Github comments

Flakey test insight

By developing Ruby, some flakey tests might be added. Launchable has Unhealthy Tests page which analyze the flakey tests. For instance, the page shows the flakiness score which express how much the test is flakiness. Let's say foo test has a flakiness score of 0.5. This means that if foo test failed against 10 different commits, that failure was not a true failure in half of the commits. By seeing this graph, we can prioritize which tests that we have to deal with. In addition to that, we can understand the test is flakey or not.

Flakey test page

Predictive Test Selection

Ruby has an extensive suite of tests, and the number of tests is expected to grow. However, waiting for all tests to pass can be time-consuming. To address this challenge, Launchable offers the Predictive Test Selection feature. Predictive Test Selection leverages machine learning to identify the right tests to run for a specific code change. By analyzing data from past test runs and considering the changes being tested, Launchable determines which tests are most relevant. Here is a execution strategy with Launchable.

  1. Initial Selection
    Launchable selects a subset of tests (let's say approximately 25% of all tests) based on the predictive analysis. These tests are executed, first.

  2. Remaining Tests
    The remaining of 75% of tests are then executed. Since the initial selection focuses on potentially problematic areas, there's a high likelihood of identifying any failed tests sooner.

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