Assessing the understandability of source code remains an elusive yet highly desirable goal for software developers and their managers. While many metrics have been suggested and investigated empirically, the McCabe cyclomatic complexity metric (CC) -which is based on control flow complexity -seems to hold enduring fascination within both industry and the research community despite its known limitations. In this work, we introduce the ideas of Control Flow Patterns (CFPs) and Compressed Control Flow Patterns (CCFPs), which eliminate some repetitive structure from control flow graphs in order to emphasize high-entropy graphs. We examine eight well-known open source Java systems by grouping the CFPs of the methods into equivalence classes, and exploring the results. We observed several surprising outcomes: first, the number of unique CFPs is relatively low; second, CC often does not accurately reflect the intricacies of Java control flow; and third, methods with high CC often have very low entropy, suggesting that they may be relatively easy to understand. These findings challenge the widely-held belief that there is a clear-cut causal relationship between CC and understandability, and suggest that CC and similar measures need to be reconsidered as metrics for code understandability.
Vinju et al. REF investigated the relationship between the shape of control flow patterns observed in Java methods to their CC metric values, proposing the concept of abstract control flow patterns (CFPs) and compressed control flow patterns (CCFPs), which allow us to produce statistical evidence that the CC metric indeed does not adequately model the likely complexity of control flow in Java methods.
What Does Control Flow Really Look Like? Eyeballing the Cyclomatic Complexity Metric
2012 IEEE 12th International Working Conference on Source Code Analysis and Manipulation
2012 IEEE 12th International Working Conference on Source Code Analysis and Manipulation
Computer Science