ACCELQ today unveiled the cloud-based ACCELQ Live test automation platform that is continuously integrated with a wide range of low-code and no-code application development and deployment platforms.
ACCELQ CEO Mahendra Alladi said the goal is to make it simpler to run complex tests across a multi-cloud computing environment.
Usage of low-code and no-code tools has greatly expanded since the start of the COVID-19 pandemic. Many organizations are now relying on these tools to accelerate a wide range of digital business transformation initiatives. The challenge they encounter is that many of these processes depend on multiple applications that have lots of interdependencies across which it is difficult to conduct tests, noted Alladi.
The ACCELQ Live platform reduces testing complexity by automatically updating itself as, for example, Salesforce or ServiceNow platforms are updated. It also provides access to pre-built codeless automation assets modeled on business processes via a live link. The company is also moving toward creating a marketplace where software vendors and service providers can build and deploy pre-built testing assets, as well.
Gartner predicts the adoption of low-code and no-code technologies will nearly triple by 2025. Testing those applications creates a major challenge as the pace of application development increases. The only way organizations will be able to keep pace is by embracing test automation platforms infused with artificial intelligence (AI) capabilities, said Alladi. In effect, ACCELQ’s ACCELQ Live represents an effort to democratize the testing of cloud and enterprise apps, he added.
As organizations increasingly appreciate their dependence on software, the way tests are being conducted is rapidly evolving. In addition to dedicated testing teams, developers and application owners are becoming more involved as responsibility for testing applications continues to shift further left. The challenge organizations face is the volume of applications that are simultaneously being constructed has significantly increased. Platforms that automate many lower-level testing functions are gaining traction as a means to enable humans to focus more of their time and energy on testing more complex functionality. The goal now should be to first rely on test automation platforms as much as possible and then employ humans to fill in the gaps as necessary, said Alladi.
It may be a while before most organizations achieve that level of test automation. However, with each passing day, it’s apparent that AI will play a larger role in application testing. The issue that many DevOps teams are now working through is how to incorporate test automation platforms within the context of a larger workflow.
In the meantime, the rate at which application testers become burned out should decline as more routine errors are uncovered by machines. It’s not likely AI will eliminate the need for dedicated testing teams any time soon, but as more rote tasks become automated there is going to be more time to focus on enhancing overall quality at a time when application environments have not only become much more distributed but also a lot more complex.