一句话：提出 CoFuzz，用探针机制增量构建故障交互图，将模糊测试从收集孤立崩溃转向揭示多故障的掩蔽、级联与协同结构。
模糊测试擅长发现单个故障，却系统性地无法揭示故障在执行中的交互：一个程序点的崩溃可能掩蔽、触发或改变其他故障的表现，导致关键的故障交互未被发现。本文提出 CoFuzz，一个交互感知的模糊测试框架，将模糊测试从收集孤立崩溃转向揭示故障交互结构。CoFuzz 采用基于探针的机制，在模糊测试过程中增量构建故障交互图 M：当在某站点 fi 检测到崩溃后，CoFuzz 临时中和 fi 并重新进行模糊测试，以暴露此前被掩蔽的故障，并将关系分类为掩蔽、级联或协同。这些交互信号指导语料库优先级排序与变异，使探索朝向故障组合而非仅覆盖代码。作者进一步提出交互覆盖率这一补充代码覆盖率的指标，并勾勒了可扩展的交互感知模糊测试研究议程，以揭示真实软件的完整故障拓扑。
Fuzz testing is highly effective at exposing individual faults, yet it systematically fails to reveal how faults interact within execution. A crash at one program point can mask, trigger, or alter the manifestation of others, leaving critical interactions undiscovered. We present CoFuzz, an interaction-aware fuzzing framework that shifts fuzzing from collecting isolated crashes to uncovering fault interaction structure. CoFuzz employs a probe-based mechanism that incrementally constructs a fault interaction map M during fuzzing: upon detecting a crash at site fi, CoFuzz temporarily neutralizes fi and re-fuzzes to expose previously masked faults, classifying relationships as masking, cascading, or synergistic. These interaction signals guide corpus prioritization and mutation, steering exploration toward fault combinations rather than coverage alone. We further introduce interaction coverage, a metric complementing code coverage, and outline a research agenda for scalable interaction-aware fuzzing that exposes the full fault topology of real software.