DDMin versus QuickXplain - An Experimental Comparison of two Algorithms for Minimizing Collections

Abstract

About two decades ago, two algorithms, i.e., DDMin and QuickXPlain, for minimizing collections, were independently proposed and gained attention in the two research areas of Software Engineering and Artificial Intelligence, respectively. Whereas DDMin was developed for reducing a given test case, QuickXPlain was intended to be used for obtaining minimal conflicts efficiently. In this paper, we compare the performance of both algorithms with respect to their capabilities of minimizing collections. We found out that one algorithm outperforms the other under given prerequisites and vice versa. These findings help to select the suitable algorithm for a given task.