Abstract
Researchers have identified several quality metrics to predict defects, relying on different information however, these approaches lack metrics to estimate the effort of program understandability of system artifacts. In this research, novel metrics to compute the cognitive complexity of a slice are introduced. These metrics help identify code that is more likely to have defects due to being challenging to comprehension. The metrics include such measures as the total number of slices in a file, the size, the average number of identifiers, and the average spatial distance of a slice. Empirical investigation into how cognitive complexity correlates with defects in the version histories of 3 open-source systems is performed. The results show that the increase of cognitive complexity significantly increases the number of defects in 93% of the cases.