Tabby: A Synthesis-Aided Compiler for High-Performance Zero-Knowledge Proof Circuits

Zero-knowledge proof (ZKP) applications require translating high-level programs into arithmetic circuits—a process that demands both correctness and efficiency. While recent DSLs improve usability, they often yield suboptimal circuits, and hand-optimized implementations remain difficult to construct and verify. We present Tabby, a synthesis-aided compiler that automates the generation of high-performance ZK circuits from high-level code. Tabby introduces a domain-specific intermediate representation designed for symbolic reasoning and applies sketch-based program synthesis to derive optimized low-level implementations. By decomposing programs into reusable components and verifying semantic equivalence via SMT-based reasoning, Tabby ensures correctness while achieving substantial performance improvements. We evaluate Tabby on a suite of real-world ZKP applications and demonstrate significant reductions in proof generation time and circuit size against mainstream ZK compilers.

Authors

Institutions

Publication Details

Journal
Proceedings of the ACM on Programming Languages
Published
2025-10-09
DOI
https://doi.org/10.1145/3763110
Primary Topic
Cryptography and Data Security
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Tabby: A Synthesis-Aided Compiler for High-Performance Zero-Knowledge Proof Circuits

Hanzhi Liu, Luke Pearson, Yanning Chen, Jiaxin Song et al.
Proceedings of the ACM on Programming Languages
Cryptography and Data Security
article

Tabby: A Synthesis-Aided Compiler for High-Performance Zero-Knowledge Proof Circuits

Hanzhi Liu, Luke Pearson, Yanning Chen, Jiaxin Song, Junrui Liu, Yu Feng, Yanju Chen, Hongbo Wen
article en

Abstract

Zero-knowledge proof (ZKP) applications require translating high-level programs into arithmetic circuits—a process that demands both correctness and efficiency. While recent DSLs improve usability, they often yield suboptimal circuits, and hand-optimized implementations remain difficult to construct and verify. We present Tabby, a synthesis-aided compiler that automates the generation of high-performance ZK circuits from high-level code. Tabby introduces a domain-specific intermediate representation designed for symbolic reasoning and applies sketch-based program synthesis to derive optimized low-level implementations. By decomposing programs into reusable components and verifying semantic equivalence via SMT-based reasoning, Tabby ensures correctness while achieving substantial performance improvements. We evaluate Tabby on a suite of real-world ZKP applications and demonstrate significant reductions in proof generation time and circuit size against mainstream ZK compilers.

Proceedings of the ACM on Programming LanguagesVol. 9(OOPSLA2)
University of California, Santa Barbara (US), University of Illinois Urbana-Champaign (US), University of Toronto (CA), University of French Polynesia (PF)
Openalex Percentile: Top 85%
Cryptography and Data Security
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Tabby: A Synthesis-Aided Compiler for High-Performance Zero-Knowledge Proof Circuits — Hanzhi Liu, Luke Pearson, et al. · Proceedings of the ACM on Programming Languages (2025) | TGRS Research Map | TGRS