JohnLyu2/z3alpha

Synthesizes efficient Z3 strategies tailored to your problem set! Repo for the IJCAI'24 paper: Layered and Staged Monte Carlo Tree Search for SMT Strategy Synthesis.

47
/ 100
Emerging

This tool helps researchers and developers who work with Satisfiability Modulo Theories (SMT) solvers to automatically find the most efficient strategies for solving their specific problem sets. You provide a collection of SMT problems, and it synthesizes a custom Z3 solver strategy optimized for speed and accuracy on those problems. This is for advanced users of SMT solvers who need to improve the performance of their automated reasoning tasks.

Use this if you are an SMT solver developer or researcher struggling to find the best Z3 strategy to efficiently solve a specific set of SMT problems.

Not ideal if you are new to SMT solvers or only need to solve general-purpose SMT problems without requiring tailored performance optimizations.

SMT-solving formal-verification automated-reasoning solver-optimization
No Package No Dependents
Maintenance 10 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 15 / 25

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Stars

23

Forks

5

Language

Python

License

Apache-2.0

Last pushed

Feb 10, 2026

Commits (30d)

0

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