Relational decomposition for program synthesis

We introduce a novel approach to program synthesis that decomposes complex functional tasks into simpler relational synthesis sub-tasks. We demonstrate the effectiveness of our approach using an off-the-shelf inductive logic programming (ILP) system on three challenging datasets. Our results show that (i) a relational representation can outperform a functional one, and (ii) an off-the-shelf ILP system with a relational encoding can outperform domain-specific approaches.