Trace-Guided Inductive Synthesis of Recursive Functional Programs - Yuan, Yongwei; Radhakrishna, Arjun; Samanta, Roopsha (PLDI, 2023)
We propose a novel trace-guided approach to tackle the challenges of ambiguity and generalization in synthesis of recursive functional programs from examples. Our approach augments the search space of programs with recursion traces consisting of sequences of recursive subcalls of programs. Our method is based on a new version space algebra (VSA) for succinct representation and efficient manipulation of pairs of recursion traces and programs that are consistent with each other. We have implemented this approach in a tool called SyRup and evaluate it on benchmarks from prior work. Our evaluation demonstrates that SyRup not only requires fewer examples to achieve a certain success rate than existing synthesizers, but is also less sensitive to the quality of the examples.