DeepAI AI Chat
Log In Sign Up

Inductive Program Synthesis via Iterative Forward-Backward Abstract Interpretation

by   Yongho Yoon, et al.
HanYang University

A key challenge in example-based program synthesis is the gigantic search space of programs. To address this challenge, various work proposed to use abstract interpretation to prune the search space. However, most of existing approaches have focused only on forward abstract interpretation, and thus cannot fully exploit the power of abstract interpretation. In this paper, we propose a novel approach to inductive program synthesis via iterative forward-backward abstract interpretation. The forward abstract interpretation computes possible outputs of a program given inputs, while the backward abstract interpretation computes possible inputs of a program given outputs. By iteratively performing the two abstract interpretations in an alternating fashion, we can effectively determine if any completion of each partial program as a candidate can satisfy the input-output examples. We apply our approach to a standard formulation, syntax-guided synthesis (SyGuS), thereby supporting a wide range of inductive synthesis tasks. We have implemented our approach and evaluated it on a set of benchmarks from the prior work. The experimental results show that our approach significantly outperforms the state-of-the-art approaches thanks to the sophisticated abstract interpretation techniques.


Combining Forward and Backward Abstract Interpretation of Horn Clauses

Alternation of forward and backward analyses is a standard technique in ...

Optimal Neural Program Synthesis from Multimodal Specifications

Multimodal program synthesis, which leverages different types of user in...

Synthesis of Procedural Models for Deterministic Transition Systems

This paper introduces a general approach for synthesizing procedural mod...

Detecting Unsolvable Queries for Definite Logic Programs

In solving a query, the SLD proof procedure for definite programs someti...

Inductive Program Synthesis over Noisy Datasets using Abstraction Refinement Based Optimization

We present a new synthesis algorithm to solve program synthesis over noi...

Program Synthesis Guided Reinforcement Learning

A key challenge for reinforcement learning is solving long-horizon plann...

Efficient Pragmatic Program Synthesis with Informative Specifications

Providing examples is one of the most common way for end-users to intera...