The HMM framing connects to change-point detection. CUSUM (Cumulative Sum) charts solve a related problem: detecting when a process parameter has shifted by accumulating deviations from an expected value.

Key difference: CUSUM assumes sequential observation and asks "when did the distribution shift?" Bayesect asks "which commit should I test next?" — active learning vs passive monitoring.

But they could complement each other. If you already have CI pass/fail history, CUSUM on that data gives you a rough change-point estimate for free (no extra test runs), then bayesect refines it with active sampling.