The evolution of recent malware, characterized by the escalating use of cloaking techniques, poses a significant challenge in the analysis of malware behaviors. Researchers proposed forced execution to penetrate malware’s self-protection mechanisms and expose hidden behaviors, by forcefully setting certain branch outcomes. Existing studies focus on enhancing the forced executor to provide light-weight crash-free execution models. However, insufficient attention has been directed toward the path exploration strategy, an aspect equally crucial to the effectiveness. Linear search employed in state-of-the-art forced execution tools exhibits inherent limitations that lead to unnecessary path exploration and incomplete behavior exposure. In this paper, we propose a novel and practical path exploration strategy that focuses on the coverage of defineuse relations in the subject binary. We develop a fuzzing approach for exploring these define-use relations in a progressive and self-supervised way. Our experimental results show that the proposed solution outperforms the existing forced execution tools in both memory dependence coverage and malware behavior exposure.