A.I. for Risk Based Testing and Production Driven Test Coverage
Category: Software Testing | Presented By: QualiTest Group
Analyzing large amounts of production data by actual users is a very good risk-based approach to testing highly complex systems based on what users actually do instead of all of the theoretical permutations of what a system may need to support.
Is software testing capable of employing A.I. approaches, or will human software testers soon be bested by computers as well?
This white paper highlights one specific approach that is driven by analyzing large amounts of production data that describes actual usage by real users through the data taken behind them. It discusses:
How A.I. can help the 5 basic sources of test coverage
Different ways in which A.I. in testing can also be used
Risk-Based Testing-Which test cases are most important and most likely to encounter failure, and how do you limit the count?