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Self-focusing genetic programming for software optimisation

Approaches in the area of Search Based Software Engineering (SBSE) have seen Genetic Programming (GP) algorithms applied to the optimisation of software. While the potential of GP for this task has been demonstrated, the complexity of real-world software code bases poses a scalability problem for its serious application. To address this scalability problem, we inspect a form of GP which incorporates a mechanism to focus operators to relevant locations within a program code base. When creating offspring individuals, we introduce operator node selection bias by allocating values to nodes within an individual. Offspring values are inherited and updated when a difference in behaviour between offspring and parent is found. We argue that this approach may scale to find optimal solutions in more complex code bases under further development.