Risk-based testing models are founded on prioritization of functional tests based on their likelihood of failure, the importance of the functionality and the weighted impact to the business if a failure were to occur. While the merit of this model is proven, it overlooks two vital factors – the structural quality of the system under test and the degree to which complex system objects and transactions have been changed in the development cycle. Join this discussion on how a more data-driven approach to risk-based test strategy is possible. Introducing intelligence about the software system to develop an informed testing strategy can dramatically improve test effectiveness and system stability and security. Learn how the early identification of system-level weaknesses and areas of high complexity can improve test efficiency while expanding coverage.
After spending over 20 years managing, developing, and deploying complex software/hardware systems for both commercial and Department of Defense (DoD) applications, Jeff founded Lighthouse in 2000 with the aim of establishing a company whose customer service was only eclipsed by the quality of its work. Armed with an encyclopedic knowledge of motivational leadership tactics and a wealth of expertise in software quality assurance (QA) processes and technical leadership, he’s a both a hands-on company leader and the primary architect of Lighthouse’s celebrated workplace culture.
In her current role at CAST, Kim creates and cultivates strategic relationships with management consultancies and advisories, enabling them with the most modern software intelligence technology. Prior to CAST, Kim ran the business relationship between D&B and IBM, focused on data analytics and IT optimization. She also worked for Gartner for over 15 years, starting as a measurement analyst and moving on Gartner Consulting along with other roles.