In recent years, the application of artificial intelligence to test automation has become an emerging trend. Test automation using AI is a hot topic among organizations. They want to automate faster, with higher quality, and with greater agility – all of which necessitates a more intelligent approach. As a result, the testing tools must incorporate more intelligence, and more team members than ever require automation skills, necessitating an increase in recruitment to meet the demand. Thus the software industry has seen a significant increase in the number of tools that claim to provide AI capabilities for test automation activities ranging from intelligent test creation and data generation to intelligent test maintenance and execution.
Unfortunately, though many tools mislead with using this broad term of AI and brandishing its usage in their applications. We have applications which offer automated understanding and testing of an application with zero manual intervention to tools that claim to fix broken scripts using machine learning.
The Promise of AI for Testing & Test Automation
These advancements in the application of AI to software testing have the potential to overcome many automation challenges. AI and its enabled technology and services can definitely aid in the implementation of autonomous software testing, but this is right now in an evolving phase with clear risks. AI can be the biggest enabler in reducing the reliance required on human efforts in maintaining automation as applications evolve and the requirement ecosystem continually changes.
There is no doubt that autonomous testing will be the norm rather than the exception in the future. Autonomous software testing that employs AI and machine learning will help in automating testing and reduce the need for human intervention. They will continually learn to drive and improve the testing over time basis the aggregated data they collect from the activities they perform.
The overarching goal of most research in this area is to build the most advanced autonomous testing tools and platforms will can build, maintain, execute, monitor, and analyse tests automatically and autonomously. In our opinion AI cannot completely replace the human part. Their best bet is in assisting the humans to help them make faster testing decisions related to test strategy, test selection and execution and automating activities that can be predictable and reliably be done. AI can certainly help to reduce the mundane and tedious tasks in development and testing by combining machine learning and statistical models with automation.
Fanatiqa and AI for Testing
Fanatiqa is poised to bring the most effective AI and machine learning-based technologies and practices to make software testing activities significantly faster and better to development teams. Unlike other existing automation tools in the market, Fanatiqa is a smart agile testing platform that builds contextual understanding of your application like a human tester does. This contextual understanding along with the resultant test data helps Fanatiqa in coming up with the best testing coverage to deliver the fastest agile testing experience one can get. Time-consuming processes like scripting, test design, test data preparation, script maintenance, and failure analysis can all be significantly reduced with Fanatiqa.
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