Aleš Pernikář, Senior Customer Success Engineer
5 min read
It is hard to imagine anything more frustrating than implementing new software features that don’t work as intended (or worse, they broke existing features in the process 👀). And on top of it all, your automated tests didn’t raise any issues. Today, users can be quick to abandon applications that don’t meet their evolving needs—fast and continuously.
There’s another side to this, one that is equally aggravating. When everything in your product works, but your tests fail, it produces false results and negatively impacts trust in both the test and product. This leads to frustration among software developers and QA teams as they scramble to fix flaky tests, which is both time-consuming and demotivating.
This is where reliability comes in.
As a whole, maximizing reliability in a test requires robust methodology, leveraging test automation, and continuous monitoring and improvement. This delivers consistent results to quickly and accurately spot software defects and avoid flaky tests.
To avoid buggy and drawn-out code development, keep reading. We will discuss what reliable and flaky tests are and look at ways to make your software tests more reliable. Finally, we will cover how to avoid costly fixes in the future.
What is Reliability in a Test?
Tests evaluate the quality of your software, but what about the quality of your tests? Unreliable tests slow down your development process, forcing you to conduct multiple test reruns and manual verification. Oh, and this doesn’t come cheap.
Reliability in a test is the extent to which test results are predictable and consistent even with external sources of inconsistency. In other words, test reliability is when running multiple tests on an application over different time periods and environments yield stable results.
So, what does a test that is high in reliability look like?
The fundamental qualities of reliability are repeatability, reproducibility, and consistency. A reliable test is constant even if there are changes in:
- Time of day
- Unexpected events
- Environment (e.g., operating system)
- System load
- Parts of the application code unrelated to the test
- External data or resources
Why Reliability in Software Testing is Crucial
Proper reliability in software testing significantly reduces ongoing maintenance costs, especially with future development. It is generally much cheaper to spot bugs and fix them immediately rather than later down the line. Having reliable testing conditions allows developers to spot erroneous behavior in a system more easily.
Flaky tests lead to significant amounts of wasted time and cost. Developers end up spending a lot of time and resources on false failures. This takes time away from important projects that support their main development goals.
Unreliable tests drag the team into rerunning tests and have a damaging wider impact on product quality and development. In fact, a study of open-source projects found that flaky tests caused 13% of failed builds.
Flaky tests tend to mask real bugs, which then continue to haunt your software, causing production issues and customer problems. In the end, if a company's software testing is not reliable, it can harm its reputation.
On the other hand, reliability can do wonders for a project's development, instilling confidence in the operation of an application. Teams can move with confidence, focusing on development rather than fixing tests and chasing non-existent problems. The result? Faster software release and user satisfaction. 
What is a Flaky Test?
A flaky test is a software test that delivers inconsistent outcomes despite no changes to the test or the code base. In other words, despite running the same identical test multiple times, it yields both failing and passing results. The testing fails to create the same outcome with each test, which undermines test quality.
Think of it as baking a cake. Each time, you use the same recipe, measurements, method, and oven temperature.
Still, the cake comes out different—sometimes good, other times bad. And the most frustrating part in both scenarios? Trying to identify the root cause is time-consuming and demanding. This undermines developers’ morale and their trust in tests.
In worst case scenarios, this can lead to a vicious circle of seeing flaky scores, getting frustrated, and ignoring the results.
If your test results are inconsistent, then you need to pinpoint what causes the flaky tests quickly. It could be:
Race conditions: When race conditions occur, it is because two things are racing to execute an action simultaneously. This could be waiting for a request to return, short timeouts, or performing multiple tests at the same time, among other reasons. Testing needs to be deterministic and completed in a certain order. If race conditions occur, things can happen that are out of the expected order and lead to flaky tests.
External factors: If there is no change in the code when a flaky test occurs, then you need to look at outside factors. In a high percentage of cases, this is because of some sort of change in the external resource. There could be a bottleneck in the network, CPU, a lack of free RAM, or local disk space. Ask yourself what’s different from one test to another.
Poor test design: A test might have an error in the arrange phase, act phase, or assert phase. It may not verify the expected state correctly, have too strict timeout, or have an error in the logic.
Lack of Isolation: One prevalent source that leads to race conditions or external resource changes is a lack of isolation. Run your test in isolation, including test data, dependencies, and environmental variables, to enhance reliability. Plus, clean any changes made so future tests start with a clean state. Leaks from one test to the next are a common root cause for flaky tests. 
How to Elevate Reliability in Your Software Testing
Now we know what causes flaky tests, and we understand why test reliability is non-negotiable. But how do you avoid test flakiness and maximize their reliability? Let’s look at some proven strategies:
1. Automation
Where possible, remove human error and interference and automate repetitive tasks to improve consistency. This gives confidence that each step executes in an identical manner every time. Tools that support parallel execution and detailed reporting can further strengthen this automation process and achieve reliable testing.
📖 Read on → Rethink Your Application Testing with an Inverted Test Pyramid
2. Blackbox Techniques
Black box testing focuses on testing software from the end-user's point of view. Testers assess functionality without ‘seeing under the hood,’ and don’t need to worry about the internal workings. Instead, tests interact with the software’s user interface or APIs to see how it performs. This helps to find problems affecting the desired functionality rather than the code execution.
📖 Read on → Core Differences Between Blackbox and Whitebox Testing
3. Continuous Integration and Testing
Continuous integration and testing ensure that tests are run regularly and consistently with new code as soon as it is produced. This helps to discover potential issues early and to isolate them in a small chunk easier for analysis.
📖 Read on → Debug Less and Deploy More with Continuous Integration
FAQs on Reliability in Software Testing
Q1) How Do I Address and Prevent Flaky Tests?
To address and prevent flaky tests, you must identify the root cause. This could be anything from race conditions to poor test design to external dependencies. Once found, you can implement strategies to increase robustness, like retry mechanisms, time-outs, or isolating tests. Continuous testing helps your team discover issues early and often.
Q2) Can Eliminating Flaky Tests Lead to Ignoring Real Issues in the System if Done Incorrectly?
Eliminating flaky tests can lead to overlooking the real defects in a system. If you design a test to be too lenient, it will always pass, but it could cover some real issues in the future. Aim for a balanced approach between test robustness and strictness.
Final Points
Every developer wants to deliver high-quality software products. This is impossible without flaky test detection and, even better, maximizing the reliability of your tests. Without trustworthy test scores it becomes hard to identify the true issues hiding in code bases.
Further down the line, you’re likely to run into more complex problems and even frustrate users when your application fails. This could be time-consuming and costly to fix.
Flaky testing can cause deployment delays as developers hunt for problems and dedicate resources to fixing the tests. In some cases, it leads to a failed build. In the worst cases, releases seem successful but because of test flakiness, they contain issues that reach production and damage user experience.
At Y Soft, we’ve engineered a new breed of test automation, an AI-powered platform that maximizes test reliability and streamlines testing. Join our user waitlist and become one of the first to experience how AIVA makes testing easy, reliable, and efficient.
