Combining the Top-Down Propagation and Bottom-Up Enumeration for Inductive Program Synthesis

We present an effective method for scalable and general-purpose inductive program synthesis. There have been two main approaches for inductive synthesis: enumerative search, which repeatedly enumerates possible candidate programs, and the top-down propagation (TDP), which recursively decomposes a given large synthesis problem into smaller subproblems. Enumerative search is generally applicable but limited in scalability, and the TDP is efficient but only works for special grammars or applications. In this paper, we synergistically combine the two approaches. We generate small program subexpressions via enumerative search and put them together into the desired program by using the TDP. Enumerative search enables to bring the power of TDP into arbitrary grammars, and the TDP helps to overcome the limited scalability of enumerative search. We apply our approach to a standard formulation, syntax-guided synthesis (SyGuS), thereby supporting a broad class of inductive synthesis problems. We have implemented our approach in a tool called Duet and evaluate it on SyGuS benchmark problems from various domains. We show that Duet achieves significant performance gains over existing general-purpose as well as domain-specific synthesizers.