Dead-End Ratio: A Behavioral Model Quality Metric for Constraint-Aware Runtime Verification

Abstract

Automated software engineering increasingly relies on behavioral models derived from execution logs to support runtime monitoring, predictive analysis, and formal verification. However, constraints derived from such models may be unsuitable for strict runtime enforcement. We investigate this issue in constraint-aware next-event prediction and identify dead-end states, where no candidate continuation satisfies the enforced safety specification. We introduce the Dead-End Ratio (DER), which measures the proportion of observed execution prefixes admitting no valid continuation under the runtime constraint specification. Experiments on two real-world event logs yield DER values of 72.1% and 33.9%. Targeted relaxation of only a few safety rules reduces DER to 2.8% and 8.3%, respectively, while substantially restoring hard-gated predictive performance. The results show that DER provides a practical diagnostic of over-restrictive runtime specifications and supports constraint debugging before deployment.