Augmented Example-based Synthesis using Relational Perturbation Properties

Example-based specifications for program synthesis are inherently ambiguous and may cause synthesizers to generate programs that do not exhibit intended behavior on unseen inputs. Existing synthesis techniques attempt to address this problem by either placing a domain specific, syntactic bias on the hypothesis space or heavily relying on user feedback to help resolve ambiguity.