Security issues in smart contracts have become increasingly prominent with the widespread use of blockchain technology. The transaction order dependency (TOD) vulnerability is a common and highly hazardous flaw that can lead to significant financial losses. Existing detection methods primarily consist of static and dynamic analysis methods but still face challenges such as high false positive rates, insufficient coverage of key paths, and reliance on fixed rules. To address these issues, this study introduces FuncFuzz, a novel TOD vulnerability detection framework guided by functional dependence. This framework uses a static analysis module to extract key functional dependence within contracts, accurately locates vulnerable areas, and enhances the specificity of generated test cases. In addition, it designs diverse transaction mutation strategies to expand test case coverage and introduces a state-based consistency determination mechanism to break through the constraints of traditional fixed patterns and dynamically adapt to complex or unknown vulnerability scenarios. Experimental results show that FuncFuzz outperforms existing tools in detecting TOD vulnerabilities, and guidance by functional dependence significantly enhances detection effectiveness.