Top 5 Things Slowing Down Your Testing Life Cycle & Software Release Process
You’ve been there before: missing deadlines, not releasing on time. The entire team waiting on testing. With unlimited permutations, constant upgrades, and apps constantly in flux, your testing team has a lot on their plate.
Testing is the key to a faster release; it should enable entire DevOps teams. Testing should be an asset. But all too often it’s a liability. Testing teams can’t keep up the pace of innovation.
Why? There’s a number of causes behind this. Here are the most common culprits of things that hold your team back.
5 Things Holding Back the Testing Life Cycle & Software Release Process
1. Tight release schedules leave less time to automate and test
What do your testing teams need to properly automate testing? Time. But when the clock is ticking, what can be done?
Because there are so many permutations to test, teams need to decide which tests to prioritize. This is why it is critical to strategize your test coverage.
Start By Prioritizing Tests
Consider adjusting your test pyramid and focus on the highly valuable and fastest test suites. You can start by prioritizing the most commonly used devices, generations, and operating systems in your geographical region. For the latest device usage data, check out our Mobile & Web Test Coverage Index.
Leverage Open Source Tools
Teams can also utilize faster test automation frameworks when working against the clock. Leverage frameworks such as XCUITest, Espresso, headless — Puppeteer, etc. Open source automated testing tools such as these can accelerate your test execution time since they have less of a complex setup. They run within the development environment and offer faster feedback.
Check Out Other Development Methods
Consider other development methods — such as acceptance test–driven development (ATDD) and behavior-driven development (BDD). Both of these methods enforce a test-first and shift-left mindset. This allows for better testing and more time to test.
2. Lack of stability and reliability in test automation
Many teams can’t trust their automated tests. They’re unreliable with constant false negatives.
Be Ready With Ready State
To combat this, teams need to make sure their target platforms are in “ready state” mode. And they also need to provide a stable lab and testing environment for these devices.
Devices are, by definition, unstable in nature. With the constant flow of new apps, new operating systems, updates, and performance issues, devices have many elements in flux. If an app fails to install, if a device has performance problems, these issues affect the stability of the device.
Stability is Key Lab Testing
The same is true for labs. Labs are difficult to create and maintain. They require constant maintenance. For those who have their own lab, they need to continuously update it. They must constantly monitor the devices to ensure their stability and testability. With DIY labs, there’s no one to help you with unstable devices.
Because of this, we recommend that you get help from the experts. Utilize a cloud-based lab with real devices to test, such as Perfecto’s Smart Lab. With 24/7 dedicated support, you’ll be sure to test on devices that are always on and always stable.
Make Your Testing Code Your Production Code
But the most important component of stability is ensuring test automation code is maintained as production code. This requires continuous test code monitoring and debugging.
It should also follow best practices for test automation creation. Some best practices include using page object model (POM), breaking the tests into logical steps for easy maintenance, and more.
With these essentials covered, automated testing can flourish at full speed.
3. Test execution management is not optimized
Investing in test creation and following best practices is the backbone of continuous testing. However, the execution should also be intelligent and under full control and governance.
Execution of tests through CI gathers feedback for business risk identification, quality assessment, and more. This should be done multiple times a day. But the value of the software iteration cycle will be lost if:
- Execution and orchestration is out of sync with the most relevant platforms that your end users are running your apps against.
- You have insufficient capacity to complete the entire cycle within the given time window.
Scale Your Lab
To overcome these challenges, teams ought to have a testing lab that can scale sufficiently with burst capabilities. It must also support all latest platforms to ensure valid test execution feedback.
Create Tests With Reporting In Mind
Test execution visibility is also key for success. As a best practice, teams should put relevant tags and hooks within their test code. That way they can easily slice and dice the data to gather high-value insights from the reports. Using advanced reporting that is AI/ML based can be a great step toward accomplishing this.
4. Evolving and maintaining test sets isn't practiced
If you’re not maintaining your test sets, you’re not testing as fast as you can. Test maintenance practices are essential to ensure that test automation continuously adds value.
Don’t Keep Old Tests Around
Test automation code should be treated and maintained as production code, and that means refactoring, updating, and even retiring obsolete test scenarios to continuously add value through testing.
You can test your automation code to see if it’s still relevant. Merge existing tests into a newer scenario that’s based on a newly developed exploratory test. This test needs to be fresh and capable of finding regression defects and extend functional coverage.
Other recommendations around test maintenance can be cross-team test code reviews through pairing and more.
Review Each Test (Again)
For critical test scenarios and the objectives behind them, teams should ask the following questions during development:
- What should the test cover? (Hint: not overly-complicated things.)
- Should it be part of each build-acceptance/CI job? (Keep the pipeline green.)
- Can it keep its reliability when it runs across multiple platforms/OS versions?
- What’s the time to develop the test and maintain it?
- What’s the coverage area? This should be top of mind.
5. Test automation tool stack isn't in synch with organizational capabilities
Another culprit that could be slowing down your software release process may be the tools you use. If the test automation framework or tools you rely on are misaligned with your team’s skillset, you could be seriously slowing yourself down.
For instance, if your team relies on Selenium or Appium for creating your test automation suites, those tests can only be created by a few team members. In order to create tests with these frameworks, coding skills are needed. In most cases, that means developers are making tests. The time spent on test creation takes them away from innovation and product development.
Choose AI For Codeless Testing
For teams that want to move faster, automate with an AI-driven codeless testing tool, like Perfecto Codeless. Codeless testing provides teams with the tools they need to generate quality test scripts more quickly. And they can more effectively maintain them.
Teams can automate the process of writing test scripts regardless of skill level — so all members of the team can participate in test creation.
But codeless test automation isn’t just for those who don’t code. It’s also a reliable, stable, and efficient way to automate tests. We know that 40% of failed automation results from scripting issues. And that has created barriers for achieving continuous testing. Now teams can overcome these challenges with the help of codeless test automation.
Now that you know what’s slowing down your testing life cycle and software release process, it’s time to go full steam ahead.
Accelerate your automated testing — and even take it to full-blown continuous testing. Continuous testing helps you assess business risks, improve code quality, and accelerate your software delivery process.
Learn how in our eBook, How to Achieve Continuous Testing in DevOps.