Highlights 2022
Program Synthesis as Dependency Quantified Formula Modulo Theory
Abstract
Given a specification F(X, Y) over inputs X and output Y, defined over a background theory T, the problem of program synthesis is to design a program P such that Y = P(X) satisfies the specification F. Over the past decade, syntax-guided synthesis (SyGuS) has emerged as a dominant approach for program synthesis where in addition to the specification F, the end-user also specifies a grammar L to aid the underlying synthesis engine. This paper investigates the feasibility of synthesis techniques without grammar, a sub-class defined as T-constrained synthesis. We show that T-constrained synthesis can be reduced to DQF(T), i. e. , to the problem of finding a witness of a Dependency Quantified Formula Modulo Theory. When the underlying theory is the theory of bitvectors, the corresponding DQF(BV) problem can be further reduced to Dependency Quantified Boolean Formulas (DQBF). We rely on the progress in DQBF solving to design DQBF-based synthesizers that outperform the domain-specific synthesis techniques. Our empirical analysis shows that T-constrained synthesis can achieve significantly better performance than syntax-guided approaches. This is a joint work with Subhajit Roy and Kuldeep S. Meel. The corresponding paper was published at International Joint Conference on Artificial Intelligence, IJCAI, 2021.
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Context
- Venue
- Highlights of Logic, Games and Automata
- Archive span
- 2013-2025
- Indexed papers
- 1236
- Paper id
- 66577251736779072