Program Defect Detection Using Sensitive Slice Semantics with Control Flow Variable Dependency

Background: Slicing technology focuses on data association behavior and is suitable for variable dependency analysis in tight defect contexts. Methods: By constructing a control flow variable dependency graph(CFVDG), performing slicing and semantic analysis and understanding, finally applied to detect defection. Results: Compared with the slicing methods based on SDG and DFG, the consumption of time and space has decreased. Conclusion: The experimental results show that this method can improve the precision of defect detection and reduce the false alarm rate, while reasonably and effectively shortening the time for graph construction and slicing, and reducing the consumption of edge storage space.