Abstract: The output results of clone code detection tool cannot be directly refactored because of the two reasons:one is the false positives of clone inconsistency related bugs detection and the other is that all the detected clones cannot be suitable for refactoring. Therefore, the output results of clone code detection tool need to be pre-processed for reducing the error checking of cloning inconsistencies defect. A pre-processing approach combing adaptive K-nearest neighbor clustering with program dependence graph is proposed in this paper to solve these problems. First, adaptive K-nearest neighbor clustering and program dependence graph are used to reduce the false positives of clones inconsistency related bugs detection. And then the refactorable clone code is identified to reduce the cost of clone maintenance. The results of the study show that our approach not only effectively prunes the false positives of clone inconsistency related bugs but also eliminates the gap between clone code detection and clone refactoring. Therefore, our method contributes to improving the quality of the software and decreasing the cost of software maintenance.