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Articles by Vincent GE
How to detect and fix flaky tests in Pytest
What are flaky tests? Flaky tests produce different results each time you run them. This means you can rerun the same CI job on the same commit 10 times and see inconsistent results. These flaky tests are the tests that fail and block your PRs when you fix a typo or bump a dependency, even though your changes couldn’t have possibly broken a test. They’re the tests that make you habitually hit the rerun job button when tests fail. Why do flaky tests occur?
What We Learned From Analyzing 20.2 Million CI Jobs In Trunk Flaky Tests - Part 2
This is part two of a blog series about building Trunk Flaky Tests. Part one covered what we’ve learned about the problem space surrounding flaky tests, like how they impact teams, why they’re prevalent, and why they’re so hard to fix. This part focuses on the technical challenges of building a product to detect, quarantine, and eliminate flaky tests. If you’re curious about what we’ve built, you can find more in the Trunk Flaky Tests Public Beta Announcement blog.
We Analyzed 20.2 Million CI Jobs In Trunk Flaky Tests: Here's What We Learned - Part 1
If you encounter problems with CI stability, it’s probably due to flaky tests. This has proven to be a recurring theme in our conversations with our CI Analytics and Merge Queue users. So, continuing with our goal to eliminate problems that engineers hate, we embarked on a journey to help developers eliminate flaky tests. Flaky tests are ubiquitous in teams with automated integration and end-to-end tests, where developers suffer in silence.
What We Learned From Analyzing 20.2 Million CI Jobs In Trunk Flaky Tests - Part 1
If you encounter problems with CI stability, it’s probably due to flaky tests. This has proven to be a recurring theme in our conversations with our CI Analytics and Merge Queue users. So, continuing with our goal to eliminate problems that engineers hate, we embarked on a journey to help developers eliminate flaky tests. Flaky tests are ubiquitous in teams with automated integration and end-to-end tests, where developers suffer in silence.
Convincing non-technical leadership to invest in DevEx.
Working as a DevRel for a DevTools company, I sometimes find myself advocating not just for our users/our company, I often do advocacy strategy for our users toward their leadership because they need to convince their org on why they're buying in. It's hard if their non-technical leadership cares about only MRR and ARR numbers (which is most of them). Wait, some teams don't run tests?
Regex, the good bits.
There are two types of developers: those who fear regex because they don't understand it and those who abuse regex to flex on their millennial teammates. The purpose of this blog is to get you somewhere in between. Know the bits that will be super useful without being dangerous. Wait, regex can be dangerous? Regex can do some spectacular things. You can write entire programs in regex. But just because you can, doesn't mean you should.
You're parsing URLs wrong.
There are somethings that you should never build by yourself. Not because it's difficult, but because it's time consuming and filled with gotchas. One of these things is URL parsing.
In technical writing, the devil is NOT in the details
I've been interviewing technical writers. What stands out about amazing candidates is that they spend surprisingly little time on the details. This surprises me and had me reflect that I look for, or rather, what makes a good technical writer. I think the assumption is that a good technical writer is made in the details. You want detailed, complete, and accurate documentation.
How I use Appwrite Databases with Pinia to build my own habit tracker
Some context I'm building a project with Vue and Appwrite called Sisyphus. Much like Sisyphus, we have many tasks that are a real uphill grind everyday. And like Sisyphus, we repeatedly push that figurative boulder up the hill each day, anyway. I built Sisyphus to help track my own habits with an UI like a GitHub commit history. Here's a GitHub commit history for reference. My inspiration I used Appwrite to implement authentication and database APIs for my app.
Multi-modal sleep intervention for community-dwelling people living with dementia and primary caregiver dyads with sleep disturbance: protocol of a single-arm feasibility trial
Sumedha Verma conceived and designed the experiments, performed the experiments, prepared figures and/or tables, authored or reviewed drafts of the article, and approved the final draft. Prerna Varma conceived and designed the experiments, authored or reviewed drafts of the article, and approved the final draft. Aimee Brown conceived and designed the experiments, performed the experiments, authored or reviewed drafts of the article, and approved the final draft.
Healthy Sleep Practices for Shift Workers: Consensus Sleep Hygiene Guidelines using a Delphi Methodology
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