A.I. – Friend or Foe? – Demystifying its implications for Testing

The demand for Artificial Intelligence in Testing is becoming mainstream. While the application of A.I. in Testing is sizeable, understanding how it can complement and make life easier for testers is the key.Amidst A.I.’s limitations, organizations need to find the sweet spot to allow their tester’s capabilities to expand. The sheer possibility of A.I. having the ability to solve complex testing challenges in a blink of an eye, which otherwise would seem difficult for us humans to get around, is something we all should embrace.How much can we trust A.I. to assist us with Testing? Dothe prospective benefits of A.I. in Testing justify our lusting appetites for it? Join me in this talk as we Demystify A.I. in software testing and help teams develop and test more efficiently and effectively, thereby creating high-quality software at speed.

Key Takeaways –

• Learn about Decision Trees and Predictive Modelling to enhance Element identification.
• Knowing details about Natural language Processing (NLP) help with action logic creation.
• Exploring Spidering A.I. to model and discover new tests
• Understand Pattern and image recognition capabilities to assist with visual Testing.
• Be aware of Synthetic Test Data generation and Minimal data preparation using the power of A.I.
• Get a deep understanding of Multi-class/ Multi-labellingand clustering algorithms for runtime self-healing
• Learn how to leverage Prognostic analysis for faster decision-making.
• Understand the benefits of Hierarchical Agglomerative Clustering (HAC) for result collation.

And lots more