IPO-MAXSAT: Combining the In-Parameter-Order Strategy for Covering Array Generation with MaxSAT Solving (Extended Abstract)

Abstract

Covering arrays (CAs) are discrete objects appearing in combinatorial design theory that find practical applications, most prominently in software testing. The generation of optimized CAs is a difficult combinatorial optimization problem being subject to ongoing research. Previous studies have shown that many different algorithmic approaches are best suited for different instances of CAs. In this extended abstract we describe the IPO-MAXSAT algorithm, which adopts the prominent IPO strategy for CA generation and uses MaxSAT solving to optimize the occurring sub-problems.