We have proposed a fault-prone software module detection method using text-filtering approach, called Fault-proneness filtering. Even though the fault-proneness filtering achieved high accuracy in detecting fault-prone modules, the detail of each fault cannot be specified enough. We thus try to complete such weakness of the fault-proneness filtering by using static code analysis. To do so, we analyze characteristics of fault-proneness filtering and a static code analyzer, PMD, by applying both methods to open source software projects. The result of comparison tells us that fault- proneness filtering can capture similar faults related to “braces” and “code size” rules of PMD. Furthermore, fault-proneness filtering can reduce false positives of rules with high false positive rate such as “design”, “naming”, and “optimization”. According to the results of analysis, we can thus construct a hybrid fault-proneness detection method using fault-proneness filtering and PMD.