Have you ever tried to build a LEGO® set only to realize—dozens of steps into the project—that you misplaced a tiny piece early on? As a result, the entire structure looks off… or worse, you can’t finish it at all. Now imagine that happening in software development. A single overlooked bug or integration issue early in the process can derail your entire release. That’s where continuous testing comes in. It’s like checking each piece as you go, ensuring everything fits correctly—before you get too far to fix it easily. In this blog, we’ll break down what continuous testing is, why it matters, and how automation and AI make it smarter than ever.
What is continuous testing?
Continuous testing is the process of executing automated tests throughout the software delivery pipeline—not just at the end. It ensures every code change is validated early, often, and automatically, so that defects are caught when they’re cheapest and easiest to fix. Think of it as embedding quality checks into every stage of development.
What is an example of great continuous testing?
Let’s say a developer is running daily SAP updates across multiple regions. Every night, automated software testing scripts run regression tests on critical business processes. With continuous testing, failures are flagged immediately, enabling fixes before users are affected—all without human intervention.
With AI-powered automation and test management software, the team maintains high coverage with minimal maintenance effort, even as applications evolve rapidly.
Why is it an important topic today?
Software delivery is shifting from scheduled releases to on-demand, always-on development. Organizations adopting agile and DevOps need testing to keep pace (see what is agile testing). Without continuous testing, teams risk releasing bugs into production—or slowing delivery to avoid risk. In a world where digital performance directly affects business outcomes, continuous testing is essential to delivering value faster and safer.
What role does automation have?
Automation is the engine that powers continuous testing. It enables testing to scale without the need for manual execution. The OpenText automation framework includes AI-enhanced object recognition, auto-maintained scripts, and test data management—reducing test flakiness and helping teams focus on building rather than fixing.
What role does AI have?
AI makes continuous testing smarter and more resilient. OpenText applies AI to detect UI changes, auto-heal broken scripts, and even suggest test scenarios based on user behavior. This dramatically reduces the maintenance overhead of test automation—a major blocker for many teams.
Is it related to continuous integration?
Yes—continuous testing is tightly integrated with continuous integration (CI). As developers check in code, CI tools trigger automated tests immediately. This feedback loop ensures every build is evaluated for risk. OpenText integrates with Jenkins, GitLab, Azure DevOps, and others to ensure testing fits seamlessly into your CI/CD pipeline.
How is it different from agile testing?
Agile testing is a broader philosophy that supports the agile development cycle with fast, collaborative, and iterative testing. Continuous testing is a tactic within agile—focused on running tests continuously and automatically. In addition, Agile testing often involves manual exploratory testing too, while continuous testing is automation-driven and pipeline-integrated.
Deliver quality software
Continuous testing is not just a best practice—it’s a business enabler. With OpenText, organizations gain the tools to deliver quality software faster, reduce risk, and simplify test management across complex, modern systems. Find out how you can deliver with continuous testing.
