Program Synthesis
Overview
Program synthesis studies how to turn desired behavior into executable code, from small transformations and algorithms to robot policies and engineering designs. Methods include enumerative and constraint-based search over domain-specific languages, learning programs from input-output examples, and language-model proposals refined through execution, counterexamples, or formal verification. These approaches can produce reusable, inspectable programs and support settings such as CAD, GPU optimization, and verified software; benchmarks such as ARC-AGI, PBEBench, and ProgramBench test how well systems infer behavior and generalize. Systems are increasingly effective when tasks have clear constraints and feedback, but open-ended synthesis remains difficult: plausible code may fail behavioral tests, miss the intended specification, or generalize poorly beyond the examples and search budget.
Latest papers
181 papers29 papers in the last four weeks, up 61% on the four weeks before. 0.2% of all new papers.