State Space Estimation for DPOR-based Model Checkers
Research Paper#Model Checking, Concurrency, State Space Estimation🔬 Research|Analyzed: Jan 3, 2026 18:22•
Published: Dec 30, 2025 05:32
•1 min read
•ArXivAnalysis
This paper addresses the challenging problem of estimating the size of the state space in concurrent program model checking, specifically focusing on the number of Mazurkiewicz trace-equivalence classes. This is crucial for predicting model checking runtime and understanding search space coverage. The paper's significance lies in providing a provably poly-time unbiased estimator, a significant advancement given the #P-hardness and inapproximability of the counting problem. The Monte Carlo approach, leveraging a DPOR algorithm and Knuth's estimator, offers a practical solution with controlled variance. The implementation and evaluation on shared-memory benchmarks demonstrate the estimator's effectiveness and stability.
Key Takeaways
- •Addresses the #P-hard problem of counting Mazurkiewicz trace-equivalence classes in concurrent programs.
- •Proposes a poly-time unbiased estimator based on a Monte Carlo approach using a DPOR algorithm and Knuth's estimator.
- •Employs stochastic enumeration to control variance.
- •Demonstrates stable and accurate estimates on shared-memory benchmarks.
- •Provides a valuable tool for predicting model checking runtime and resource allocation.
Reference / Citation
View Original"The paper provides the first provable poly-time unbiased estimators for counting traces, a problem of considerable importance when allocating model checking resources."