Adaptive Event Analysis™
AEA™ is our custom AI engine. It powers all the core functionality of our platform.
It employs AI and Machine Learning to look deeply into applications, enabling zero-hassle maintenance in a visual environment. No matter how much your site changes, AEA™ autonomously identifies and updates your tests so you can deploy your product on time and with confidence.
Every element in your app is tagged by a combination of visual specs, page location, Xpaths, functionality, server response, NLP
Responsive sites render differently but certain elements stay related to each other. We use that to help identify the elements
AEA™ creates a complete model of your system, that virtually eliminates the need for test maintenance to free up test engineer time
The benefits of AEA™
Unique fingerprints for elements
AEA™ builds a detailed fingerprint for every element in your UI. This allows it to identify elements even if they are moved, restyled, and renamed. This makes it even more powerful than a human tester.
Deep knowledge of your UI
AEA™ creates complex composite models of your UI. This allows it to understand what each element actually does, not just what it is.
Test maintenance is a real time-sink for QA engineers. But AEA™ enables self-healing tests because it knows how your UI is really working.
Root Cause Analysis
One of the most advanced features of AEA™ is its ability to track back to the actual cause of a test failure. This is especially critical in complex systems where data changes and external factors can trigger test failures.
Identifying a failure is only half of the problem. AEA™ also uses its knowledge of your previous test runs and test procedures to try out fixes. It assesses the most likely and presents this to you for approval in a 1-click update.
We view AEA™ as the brains behind our intelligent test agent.
With AEA™, our data scientists are pushing the state of the art for intelligent test automation. The important distinguishing factor is that it combines different forms of machine learning with computer vision, template recognition, and natural language processing. This approach of using boosting and other advanced techniques sets AEA™ apart. Importantly, AEA™ is not a static system. It is constantly evolving and learning. It operates at three levels. At the individual test level, it learns each time the test proceeds and updates its understanding of the aims of that test. At the system level, it builds an ever more complete model of your whole application. Globally, it learns how UIs in general work, effectively becoming an expert in best-practice UI/UX design.
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The Functionize platform is powered by our Adaptive Event Analysis™ technology which incorporates self-learning algorithms and machine learning in a cloud-based solution.