Flaky tests are viewed as a series of automated software tests.
The results of the tests are not defined.
Sometimes, they work and stop working automatically, they are unpredictable.
Usually, a flaky test is defined as a kind of test giving random results without making changes to the code.
However, several factors can create unstable test results, like instabilities in environments, using old test data to run tests, issues related to time zones, and reliability on the implementation of the test.
Furthermore, a flaky test lowers the speed of the CI/CD pipeline and degrades the confidence required in the testing process.
It is advisable not to depend upon the results of the flaky tests. Hence, a successful test run doesn’t necessarily mean error-free results.
To detect flaky tests, you must make a comparison between other test runs. Manually, this examination will be a time-consuming process to perform tests. However, some CI servers can identify flaky tests effortlessly.
Therefore, discovering flaky tests is the initial step for managing and keeping everything in moderation. For assurance, it’s vital to run tests even after getting results.
What is a Flaky Test?
A flaky test can be explained as testing that produces random results.
They are known to produce uncertain results, failing or passing randomly.
During testing, it didn’t support improvements in the system.
In comparison to dependable tests giving consistent and accurate results, flaky tests generate inconsistent results. Thus, such inconsistency can be challenging for software developers.
Features of the Flaky Tests
Some of the common features of the flaky tests are mentioned below:
1. Irregularity:
The flaky tests produce unpredictable results, and it becomes tough to decide whether it has passed or failed in the testing process.
Thus, with the shift in the status from pass to fail randomly without a single indication of the upcoming results.
2. Unpredictable Fail/Pass Title:
The flaky tests are viewed as uncertain because the pass or fail status of flaky tests is random. Such disability degrades the quality of the software.
At one moment, the status is displayed as Fail, and at the other moment, it changes to Pass. Before concluding, it is crucial to verify the results again and again.
3. Dependency:
It is tough for flaky tests to work under extreme factors related to network conditions and resources.
Usually, it increases the tendency to generate uncertain results.
How to Identify a Flaky Test?
Usually, discovering flaky tests is considered a troublesome activity. Hence, some of the basic ways to detect flaky tests are as follows:
1. Reattempting Failed Tests:
When a test fails on the initial attempt but passes on the next attempt without changing the code or environment of the test, then, you can consider the test as a flaky test.
2. Performing Tests Simultaneously:
In certain cases, when tests are run alone, they give pass status.
Simultaneously, when multiple tests are run in parallel, they fail.
Thus, a flaky test cannot work with other tests running parallel. Hence, performing various tests together can create issues.
3. Conducting Tests In Various Environments:
Assumedly, when a test easily passes in one environment but fails to do the same with different environments having distinct settings and resources.
Then, it may indicate an uncertain environmental problem.
4. Examining Test Results and Logs:
During multiple attempts, when a test generates unstable and random results or logs. It highlights the uncertain nature of the test.
5. Utilizing Frameworks and Tools:
In the digital world, there are numerous tools and frameworks offering test observability services.
Among them, Testsigma ranks best in the market, it helps in identifying and fixing flaky tests seamlessly.
Best Practices to Fix Flaky Tests
To fix tests like flaky tests, one should have a proper understanding and in-depth knowledge of the language code, the types of tests that are being performed and the system that is under test.
However, some generic methods can be employed by us to fix flaky tests. Some of such generic methodologies are discussed below:
Eliminate Dependencies by Isolation of the Test
We can use the process of isolation where the test does not rely on or depend on any exterior factors. Neither does it affect any external factors or any other kinds of tests.
One can use fake stimulators, stubs, mocks, etc to bring dependencies to the lowest. In this process, we need to use disposable resources for each test that is being performed.
Along with using disposable resources, we also need to ensure that we clean or reset the state after each test run.
Elimination of Randomness
While testing the system, we can ensure that it is free from reliance on any unpredictable or random elements or factors.
In this process, make sure to use fixed times, UUIDs, predefined values for dates and so on. In this process, one generates or processes data using deterministic algorithms.
Increase the Robustness of the System Software
We need to make sure that different scenarios and situations can be handled by the test.
To deal with issues like performance issues, network issues, etc we can use retries, waits or timeouts.
Take the help of assertions that check for various pattern ranges, or approximations.
To ensure that flaky tests are more sound, one can verify all the aspects of the outcome using assertions.
Simplify the Logic of the Test Script
It is important to create accurate and clear tests.
You can utilise logos, comments and illustrative titles for explaining purpose and characteristics of the tests.
Also, it is recommended to incorporate reusable codes for the tests and avoid errors, and bugs in those codes.
Conclusion
In the final analysis, we can visualize flakey tests as a series of tests giving random results.
However, by considering every issue faced in the testing process, Testsigma is an excellent platform that provides a perfect solution for managing flaky tests that help in automating the software in which our system operates.
Also, Testsigma can contribute to optimising your test performance.
It detects flaky tests automatically.
In this article, you have learnt about flaky tests and discovered ways to fix issues related to flaky tests.
Also Read: The Importance of Mock Tests in CAT Preparation: SuperGrads’ Approach to Success
