How AI-based Testing Fits in Your Software Testing Maturity Model
AI-based testing offers a powerful boost to your software testing maturity model (TMM).
Understanding Your Software Testing Maturity Model
Software testing maturity models offer a roadmap for ongoing improvement in testing processes.
How artificial Intelligence (AI) and TMM can Work Together
By integrating AI-based testing techniques, organizations can supercharge their journey, achieving significant gains in efficiency, effectiveness, and automation.
Let’s Delve into the Advantages of Leveraging AI and ML within TMM Levels.
Level 1 – Initial
AI-based testing can automate repetitive processes such as test case generation and execution
Level 2 – Managed
At this stage, using AI-based testing methodologies offers a chance to advance testing procedures and promote ongoing development
Level 3 – Defined
In this phase, standardized testing procedures, metrics, and defect tracking are in place.
Level 4 – Measured
AI-based testing is used to analyze to identify trends, drive data-driven decision making, optimize resource allocation, and improve testing effectiveness.
Level 5 – Optimization
At this level, teams have an established continuous improvement, innovation, and excellence in testing practices.
Benefits of AI Testing at Every Stage in TMM
AI enables you to continuously improve your testing procedure, getting rid of redundancies and making sure your automation efforts are as productive as possible.
How Webomates can Help
When you need guaranteed test results quickly – and first-time right – Webomates delivers a cost-effective, fast, and accurate approach.