New feature: SofySense – Manual test case & test results AI generator to help you speed up your testing process. Try it today.  

Sofy launches product feature suite to deliver effortless test maintenance and ensure continuous precision – learn more.

sofy logo

The Testing Bottleneck: Is It Necessary?

Testing doesn't have to be the bottleneck. If you're struggling during testing, there are changes you can make.

Have you ever experienced a testing bottleneck? Or have you ever blamed testing for development delays?

Sure you have.

As essential as testing is, it’s a challenge to manage test cases alongside development. A single failed test can tack on days to the timeline. 

In this post, we will explore why testing is often viewed as a bottleneck and what you can do about it.

What is a bottleneck, anyways?

A bottleneck simply refers to a point in a process where demand exceeds capacity. When a bottleneck is severe enough, it causes delays in the rest of the process. When testing is the bottleneck, you’re waiting for work to be released (to production) and can’t process more work until testing is complete. The longer testing takes, the slower the entire process is.

Bottlenecks are unavoidable. There will always be points in the process that are slower than others. But with the right adjustments, it doesn’t have to be testing.

One thing is for certain, no matter how bad the bottleneck becomes, cutting corners during testing can only lead to disaster.

Common reasons for a testing bottleneck 

There are a few common reasons why testing can bottleneck the development process:

An over-reliance on manual testing

Even the most mature organizations resort to manual testing. Sometimes it’s the easiest way to get something done. Unfortunately, it takes a long time to execute manual test cases, record results, and provide feedback. By the time you’ve identified an issue, more work is added to the backlog. Manual tests are subject to misinterpretation and errors. Everyone tests a little differently and slight differences in interpretation can lead to vastly different results. 

There’s also the time it takes to write manual test steps and update test steps with each release, adding hours of overhead to deployments.

Not enough resources

Many development teams don’t have a dedicated QA team. Instead, they rely on a subset of developers and regular business users to help create, manage, and execute test cases. The issue is that organizations don’t have the capability to scale to demand, and when testers are needed, developers are pulled from other important work streams to help write test cases, affecting other parts of the process. 

Increasing complexity

As an app’s functionality grows, complexity and technical debt build up. If development teams aren’t continuously working with testers, they’ll be left scrambling to reach code coverage after every change. When changes exceed testers capacity, excess cases lead to a bottleneck.

Device fragmentations

The device world is rapidly growing. With different devices, versions, screen sizes, and operating systems, it’s now imperative that app developers are testing on multiple devices. However, the time it takes to acquire, set up, and test on devices could add serious time to testing and ultimately delay releases. It’s also necessary to create, adjust and maintain test cases for each operating system. When an OS releases a new version, developers need to retest to ensure continuing compatibility.

Keeping up with regression testing

A small change in the application code-base could break existing regression tests. It’ll then be up to the app developers to track the issue and make changes to all existing test cases that share the same dependencies. This back and forth adds potential time to the app release. 

Testing: A misplaced blame

In most cases, testing simply exposes weaknesses in other parts of the development process. If your tests are consistently failing, it could mean poor development quality or a lack of communication between development and testing teams. So before you put all the blame on testing, consider that it’s a team effort.

The solution for bottlenecks? Smash them! Image: Sofy x Yoyon Pujiono, Shutterstock

What to do differently

The solution can often be to simply do things a little differently or to choose more advanced processes:

Automate test cases

Manual testing isn’t completely avoidable, but it can be greatly reduced by automating test cases. There are several free, open-source tools and frameworks that let you write test cases using different languages. Some popular tools include Selenium, Appium, and Robotium. We’ve written at length about some of these tools.

By automating test cases, you remove the chances of inconsistent test execution and the mistakes that often come as a result of manual testing.

Consider going scriptless

You can skip the test script all together, and leverage the magic of no-code. Scriptless testing tools let you record and automate test cases without the use of code. These tools work by recording your interactions with UI elements, checking for assertions, and playing them back on command. 

Now, Sofy is using AI to help create test cases even quicker.

Sofy is a scriptless testing tool that lets you create sophisticated test cases with a few clicks. In fact, with Sofy, you can create a test case in minutes. You can even reuse previous test cases by creating templates to compose tests faster. 

By leveraging a scriptless test tool, you can save the time spent writing and maintaining tests. You’re also able to tap non-technical resources, which reduces the chances of being bottlenecked by resource constraints.

Test on multiple real devices

Nothing can replace real device testing. Testing on a live device offers much greater assurance than emulators or simulators.

The problem? 

Real device testing is traditionally expensive, especially if you plan on acquiring and maintaining the devices yourself. 

With Sofy, you can acquire a real device from our device cloud. With the device cloud, we host and maintain the device for you so you can begin testing immediately. Each device you acquire comes with a clean instance with your application already installed. When you’re done writing your test case, you can automate it and run it across multiple live devices.

Testing on plenty of real devices can reduce the likelihood of finding device specific bugs in production.

Get help from AI

The emergence of AI and machine learning in testing has made it much easier for QA teams to quickly deliver stable test cases. AI can recommend test changes, identify potential issues, and automatically make adjustments based on existing code coverage.

Sofy recently announced SofySense, a revolutionary digital assistant powered by OpenAI’s generative AI technology. SofySense can convert manual test steps into automated tests, provide advanced insights and analysis, and serve as a guide for testers.

No more digging online to discover best practices or debug issues. Just ask Sofy Bot and get an answer.


Every process has a bottleneck but you don’t have to experiencing a testing bottleneck. With the right tools and approach, you can easily avoid any kind of testing bottleneck issue. Try using automation, adopting no-code, and leveraging the power of AI to help alleviate testing bottlenecks and start delivering serious value.

Disclaimer: The views and opinions expressed above are those of the contributor and do not necessarily represent or reflect the official beliefs or positions of Sofy.