GreeDDy: Accelerate Parallel DDMIN
Dániel Vince, Ákos Kiss · 2024
One of the most important algorithms in the field of automated test case minimization is the minimizing Delta Debugging (DDMIN) algorithm. It is used with preference because it works on any kind of input without information about its structure. In this paper, we focus on the parallelization of DDMIN. We discuss its stability issues and outline a potential solution to it. Then, we discuss an idea to speed up parallel DDMIN without compromising the minimality guarantees of the algorithm. We evaluate this algorithm variant, named GreeDDy, on a publicly available test suite.