By Robert Stoddard
Software reliability practice continues to evolve from a early focus on the modeling of software test failures for reliability estimation to the modeling of pre-test activities and software attributes for reliability prediction. The speaker believes the next major evolutionary step in software reliability research and practice will come with the application of causal learning. Causal learning has become a practical and exciting field rooted in matching methods employed long before Ronald Fisher created Designed Experimental methods in the 1930’s and 1940’s. This webinar will share the recently matured landscape of causal learning consisting of causal discovery and causal estimation. A brief description of causal methods, algorithms and modern publications will be shared along with recommendations on how reliability engineers might pursue learning and adopting causal learning.