Mutant Density: A Measure of Fault-Sensitive Complexity
This addresses the need for more accurate fault prediction in software engineering, though it appears incremental as it builds on mutation testing and complexity metrics.
The authors tackled the problem of existing code complexity metrics not directly accounting for fault-proneness by proposing a new metric called mutant density, which counts possible mutations per line to measure fault-sensitive complexity, and demonstrated its application in analyzing real-life software projects.
Software code complexity is a well-studied property to determine software component health. However, the existing code complexity metrics do not directly take into account the fault-proneness aspect of the code. We propose a metric called mutant density where we use mutation as a method to introduce artificial faults in code, and count the number of possible mutations per line. We show how this metric can be used to perform helpful analysis of real-life software projects.