Drill and Join: A Method for Exact Inductive Program Synthesis

In this paper we propose a novel semi-supervised active machine-learning method, based on two recursive higher-order functions that can inductively synthesize a functional computer program. Based on properties formulated using abstract algebra terms, the method uses two combined strategies: to reduce the dimensionality of the Boolean algebra where a target function lies and to combine known operations belonging to the algebra, using them as a basis to build a program that emulates the target function. The method queries for data on specific points of the problem input space and build a program that exactly fits the data. Applications of this method include all sorts of systems based on bitwise operations. Any functional computer program can be emulated using this approach. Combinatorial circuit design, model acquisition from sensor data, reverse engineering of existing computer programs are all fields where the proposed method can be useful.