Discriminating Fixture Coverage in Agent-Infrastructure Verification Suites

2026-10-02

AI Summary

This study addresses the deficiency of surviving mutants in intelligent agent verification suites caused by insufficient test fixture coverage. Through mutation analysis, it exposes blind spots in conventional verification and identifies two failure modes: unactivated execution and state invisibility. A seven-dimensional input space enumeration method is proposed, combined with a pre-registration prediction mechanism to precisely supplement missing fixtures. Furthermore, a systematic verification framework is constructed by integrating mutation testing, runtime monitoring, and differential coverage analysis. Experimental results demonstrate that the proposed approach successfully kills all five surviving mutants, significantly enhancing both the fault-discrimination capability and the completeness of the verification suite.

Abstract

Invariant suites and runtime monitors increasingly gate agent deployment decisions, and the evidence offered for any particular suite is almost always a single observation: it passes an implementation believed correct and fails one believed broken. We measure what that observation is worth. Applying mutation analysis to an invariant suite for a multi-session agent state-projection layer, we first find that this standard validation certifies a suite in which a first-order mutant removing event-identity deduplication survives every check. We then freeze the repaired twelve-check suite, record its hash, and run it once against ten mutants specified by an adversarial reader who designed none of its fixtures: it kills five. Instrumenting the five survivors against the reference shows they fail in two distinct ways, not one. Three are never activated, because no fixture supplies an input on which the mutated code behaves differently at all. The other two corrupt internal state that no oracle in the suite can observe. The two modes need different repairs, and neither is visible from a pass/fail report. Treating the missing inputs as a coverage question, we enumerate seven discriminating dimensions of the input space, register in advance which are uncovered and which survivors they should explain, and add one fixture per uncovered dimension while reusing the existing oracles verbatim. All five survivors then die, each to the check written for its predicted dimension. We report this as a repair result on the same challenge set rather than a second held-out estimate, and give the artifact, including the frozen hash, the registered predictions, all mutants and the run logs, so the distinction is checkable.

Problem

• agent-infrastructure verification
• mutation analysis
• fixture coverage
• invariant suites
• discriminating inputs

Innovation

• mutation analysis
• invariant suite
• fixture coverage
• discriminating dimensions
• agent-infrastructure verification