Predictive Analytics in Test Management

Daniel Geater, Qualitest

Global software developers are in a double bind: They’re under pressure to release new or upgraded applications continuously, while apps have become increasingly feature-rich and complex. Traditional QA processes, including manual risk-based testing (RBT), can’t keep up, and the bottlenecks are getting bigger.

This case study-based presentation will examine how organisations can use AI and automation to transform test planning into a faster, data-driven process that:

  • reduces business risk
  • serves as a key enabler to apply shift left/shift right strategies
  • supports quality engineering
  • leads to better, more accurate decisions, helping the organisation move faster, with confidence.

Objective of the talk

Audience members can expect to learn, from a real-life example, how AI can be harnessed to make testing smarter and more accurate and become familiar with best practices/potential dilemmas in applying predictive analytics to risk-based testing.

Required audience experience

The audience should have a basic understanding of software quality assurance, testing and AI concepts.

Track 1
Location: Mountbatten Date: October 1, 2019 Time: 3:45 pm - 4:30 pm Daniel Geater, Qualitest Daniel Geater, Qualitest