Locating core modules through the association between software source structure and execution

To improve software quality, the source code that composes software has to be improved, and improving the important code that largely affects the software quality should be a cost-effective method. Static analysis defines important codes as those that occupy important positions in the source network, while dynamic analysis defines important codes as those with high execution frequency. However, neither method analyzes the association between network structure and execution frequency, and both have their disadvantages. Thus, this study analyzed the association between source network structure and execution frequency to solve their disadvantages. The source function of Notepad++ was analyzed, and the function ranking was derived using the association between network structure and execution frequency. For verification, the Spearman correlation between the newly derived function ranking and the function ranking of the network and execution frequency obtained with the conventional method was measured. By measuring the Spearman correlation, the newly derived function ranking had strong correlations with execution frequency and included the network structure’s characteristics. Moreover, similar to the Pareto principle, the analysis showed that 20% of Notepad++‘s functions could be categorized as important functions, largely affecting the software’s quality.