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


  • Irene Hiess SBA Research, MATRIS Group
  • Ludwig Kampel SBA Research, MATRIS Group
  • Michael Wagner SBA Research, MATRIS Group
  • Dimitris E. Simos SBA Research, MATRIS Group


Combinatorial Optimization, Search In Boolean Satisfiability, Constraint Search, Real-life Applications


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.