From Verification to Herding: Exploiting Software's Sparsity of Influence

2026-03-11

AI Summary

Traditional software verification is costly and struggles to scale to complex systems. This work proposes a novel paradigm termed “herding,” which exploits the “influence sparsity” inherent in software state spaces—where a small subset of key variables disproportionately governs system behavior—to circumvent the need for heavyweight formal modeling and solving. To operationalize this insight, we introduce EZR (Efficient Zero-knowledge Ranker), a model-agnostic algorithm that employs lightweight random sampling to perform goal-directed search and directly identify critical control variables. Empirical evaluation across dozens of tasks demonstrates that EZR achieves 90% of peak performance with only 32 samples, substantially reducing testing costs while significantly improving efficiency.

Technology Category

• Search and Optimization: Sampling/Simulation-based Search
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories
• Reasoning under Uncertainty: Stochastic Optimization

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems

Abstract

Software verification is now costly, taking over half the project effort while failing on modern complex systems. We hence propose a shift from verification and modeling to herding: treating testing as a model-free search task that steers systems toward target goals. This exploits the"Sparsity of Influence"-the fact that, often, large software state spaces are ruled by just a few variables, We introduce EZR (Efficient Zero-knowledge Ranker), a stochastic learner that finds these controllers directly. Across dozens of tasks, EZR achieved 90% of peak results with only 32 samples, replacing heavy solvers with light sampling.

Problem

• software verification
• sparsity of influence
• herding
• model-free search
• testing

Innovation

• herding
• Sparsity of Influence
• model-free search
• EZR
• software verification