No More Flaky Tests!

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In this talk, you’ll learn what flaky tests are, the importance of deterministic tests, the collateral effects of non-deterministic tests, the motives why tests can become brittle, and finally, what to do (and what not to do) when you find flaky tests

Walmyr
Walmyr
29 min
07 Dec, 2023

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Video Summary and Transcription

The Talk discusses the harmful effects of flaky tests and the importance of writing deterministic tests. It provides strategies for identifying and addressing flaky tests, including using test retries and burning tasks on CI. The Talk also emphasizes the need to avoid arbitrary wait times and handle dependencies when writing end-to-end tests. It highlights the importance of running tests in CI and leveraging tools like Cypress Cloud for test replay and debugging. Additionally, it suggests mocking externals to improve determinism and prioritizing the work to address flaky tests promptly.

Available in Español

1. Introduction

Short description:

I'm here on the stage to talk about No More Flaky Tests. Have you ever encountered a bug that works on the developer's machine but fails in the continuous integration pipeline? Let's discuss the importance of writing deterministic tests.

I'm so happy to be here. I was the MC the last two years, and now I'm here on the stage. I'm a bit nervous, but I hope you like the talk I prepared for today, which is called No More Flaky Tests. And I want to ask you if you have ever been in a situation where you found a bug, and you asked the developer, and they said, it works on my machine. Always on fire, but it works on my machine. And then you think, should we deploy your machine so our users can use it? But what about that test that passed locally on your computer? And when it started running in the continuous integration pipeline, it started failing sometimes. So if we are writing the tasks, we are a bit guilty as well.

2. The Harmful Effects of Flaky Tests

Short description:

Flaky tests are harmful and more harmful than having no tests at all. They decrease confidence in the test suite, increase the number of unfound bugs, and increase debugging time and software engineering costs. They also increase delivery time and decrease the perceived software quality. Tests can become non-deterministic due to shared environments between manual and automated testing and waiting times caused by network requests.

And if we say that we should deploy the computer of the developer in production, we should also take care of the tests that we write so they are deterministic. Because a flaky test, this is an analogy that I really, I found really nice that Brian Mann from the Cypress team mentioned that a flaky test is like a grenade waiting to explode. And so I want to give you my definition of what is a deterministic task first, which is that given the same initial system conditions, when a test is run with the same inputs, it will always return the same results, same output.

In contrast, the definition of a non-deterministic test is that given the same initial system conditions, when the test is executed with the same inputs, it will return different results. So it is that test that there are no change in the code or of the application or the testing code and sometimes it passes, sometimes it fails, sometimes it fails in the first try and then you retry and it passes and you don't know why.

And I want to tell you that flaky tests, they are harmful and they are more harmful than having no tests at all. I had to gray out a few boxes here because I don't have time to talk about all the side effects of flaky tests, but a few of them are that if you have flaky tests, also known as non-deterministic tests, there are some side effects to it. One of them is that it decreases the confidence in your test suite. So if you have a team that depends on the results of your tests to know if they can move forward with the next thing or if they have to fix something, but the tests fail, they spend a lot of time debugging and they don't know and then when they find out what was wrong with the test, then you lose the confidence.

And you also increase the number of unfound bugs because when developers lose confidence on the test suite, what happens is that if the test is failing, they will say, you know what, this test is, they are always failing. So if it's failing, it's just another failing test. Let's move on. But sometimes the test might be finding a real bug. And because you don't trust the test suite, you just leave the bug. And who will find is the user. I already mentioned, it increases debugging time. So you spend a lot of time trying to understand why the test is failing. And when you realize that it was just a test that was not well written, or it wasn't robust enough. Since time is money, it increases software engineering costs as well.

And with agile methodologies, what we want is to decrease the delivery time to make it as short as possible to deliver new functionalities to our users. But if we have flaky tests, what we do is we increase delivery time. And finally, we decrease the perceived software quality of the software we are writing. And there are some reasons why tests can be or become non deterministic or flake. A few of them is where when you share environments between manual testing and automated testing. So you are at the same time that an automated test suite is running, for instance, for a pull request that had been opened in an environment that is shared with someone that is running some manual testing, someone changed the configuration that the automated test fails. And when you go and investigate, you notice that it was just a configuration that someone manually changed. Another reason is waiting times. Sometimes because of network requests, things take time to proceed. And you would do something like if you use Cypress, for instance, you could do something like a Cy.wait, 10,000 milliseconds. That's not the way to go.

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