The Current State of Open Source Test Automation Tools
Open source automation tools such as Selenium have been the workhorses of QA automation for decades, especially for web apps. With the birth of open source in the 1990’s, there was an explosion of activity around the potential of open code to deliver high-value tooling that would make software development teams more productive and cost-effective.
But as we have learned, open source tools come with shortcomings that need to be understood with eyes wide open when assessing them for adoption into your DevOps. New models, technologies, and approaches to QA automation are putting open source tools in the rearview mirror for many organizations as they provide superior value in many aspects of the QA function.
1. Consider the Case of Selenium
Selenium and similar open source tools are frequently outpaced by commercial offerings that are taking radically advanced approaches to QA practices. As a result, their advancements fall behind the pace of commercial solutions, such as handling newer, modern web libraries. And libraries like Angular and React create an even greater burden for coders trying to figure out how to incorporate these elements, since they aren’t supported in the Selenium IDE, so testing these libraries requires the team to have coding capabilities.
2. The Unrealized Economic Promise of Open Source QA Tools
Enterprises have thought they would save money by adopting open source development tools, but in the end, the people costs may dwarf any such promises. QA teams may require more coding skills than with a codeless or low-code commercial tool approach. They may also find that they have to invest more effort in maintenance because the tests constructed with open source tools don’t have the resilience or self-healing features of AI-enabled commercial tools. Plus enterprises should not overlook the bells and whistles, like out-of-the-box reporting, that come with commercial packages. The costs, burdens, and risks around that headcount and skills outweigh the cost and simplicity of merely buying a commercial system that comes with the features and functionality to deliver against enterprise expectations. In the end, nothing is free, which is why open source QA tools have proven to be very expensive for large QA teams.
3. The Reliability Factor with Open Source Tooling
Another factor that detrimentally affects open source test automation tools is the community approach to training and customer support. Support uncertainty can compound problems when teams face pressure to ship and an issue with the tool arises. Open source community support is often hit or miss and can not be relied upon to help. Compare this to a support contract with a commercial vendor who is obligated to respond within minutes to address your needs. There are also vendors that include some level of support in their base packages.
4. A Quantum Leap in QA Productivity with Test Automation
AIQ, our AI-powered test automation and continuous testing system, provides more than an order of magnitude improvement in benefits versus the open source competition. First, it automates in one solution the lion’s share of work a QA team is tasked with: functional & regression testing, performance & load testing, and compatibility & security testing across numerous technology platforms. The number of open source tools needed to address all those areas of the QA function alone would create an IT burden that is hard to justify.
But more importantly, AIQ is powered by our AI model, making it an independent, autonomous member of your QA team. With a small investment in training the AI about your app, AIQ can spin up dozens or hundreds of AI’s to test your app within minutes. It can accurately report your test coverage, log issues, and provide test scripts for future test cases. Our AI is so sophisticated, AIQ truly delivers on the promise of continuous testing to your CI/CD pipeline. It’s as if you’ve given your QA managers more testers who are all A players.
If your team is ready to retire legacy automation tools and adopt a future-forward AI tool in your QA function, now is a great time to get a live demo of AIQ on the calendar. We would be happy to show you how AIQ and its advanced machine learning model can increase the productivity of your QA function in ways traditional open source tools can’t begin to address. Request a meeting today!
And to learn more about AI-driven autonomous and continuous testing, download our eBook here.
