Leveraging AI for Testing

Owned by Krishna veni
Last updated: Nov 25, 2024
1 min read

Introduction:

The Software testing has been going through its own automation journey. It has evolved from manual testing to functional automation, to smart automation and now, Intelligent automation (e.g., AI & Gen AI) and Codeless automation (e.g., low code, no code).

Testing activities like test data creation, test reporting, regression testing, etc. are heavily automated. But test case review and test case execution remain primarily manual. Test case creation, test data creation and test reporting have high potential for AI & Gen AI adoption. The integration of Artificial Intelligence (AI) into Quality Assurance (QA) is revolutionizing testing methodologies thereby improving test efficiency and test coverage.

Goals:

We started this project with a vision of how we can improve our daily & repetitive testing activities by leveraging AI. As a part of this our areas of stress would be both functional and automation testing activities as follows,

  1. Intelligent Test Case Generation

  2. Dynamic Test Execution

  3. Enhanced Defect Prediction

  4. Self-Healing Test Scripts

  5. Smart Test Prioritization

  6. Continuous Integration Support

And we will work on how we can improve on API testing as well.