Using genetic improvement & code transplants to specialise a C++ program to a problem class

Abstract. Genetic Improvement (GI) is a form of Genetic Program-ming that improves an existing program. We use GI to evolve a faster version of a C++ program, a Boolean satisfiability (SAT) solver called MiniSAT, specialising it for a particular problem class, namely Combi-natorial Interaction Testing (CIT), using automated code transplanta-tion. Our GI-evolved solver achieves overall 17 % improvement, making it comparable with average expert human performance. Additionally, this automatically evolved solver is faster than any of the human-improved solvers for the CIT problem