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shows a few more steps in generating the Source Code Graph from the commit patch shown in Figure 4. A segment from the XML representation of source code lines shows the hierarchy of tokens converted into a graph. Two graphs in this figure show the change in code structure in that commit operation. As a developer may perform multiple changes (addition/ deletion) in a single commit, it could generate multiple graph representations in such commits. We took the union of graphs to form a single graph of a single commit for extracting graph attribute-based feature values. We use those feature values as additional features to represent commits in bug visualization and its ML-based classification to verify our research questions and hypothesis. We then calculated its attribute values to be used as additional feature values to represent those commits. The key steps in this section are as follows.
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The most common use of data visualization is to minimize the complexity for proper understanding. A graph is one of the most commonly used representations for understanding relational data. It produces a simplified representation of data that is challenging to comprehend if kept in a textual format. In this study, we propose a methodology to utiliz...
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The most common use of data visualization is to minimize the complexity for proper understanding. A graph is one of the most commonly used representations for understanding relational data. It produces a simplified representation of data that is challenging to comprehend if kept in a textual format. In this study, we propose a methodology to utiliz...