Statistical methods for the analysis of software metrics data

Abstract

The authors present case study applications of statistical methods for the analysis of software metrics data which recognize the discrete nature of such data. A procedure is also described which allows a component of complexity independent of size to be extracted from the usual Halstead's metrics and McCabe's cyclomatic number. The methods described are different from the usual regression and non-parametric methods previously applied to software metrics. With the software quality practitioner in mind, the paper explores how these new methods are helpful in understanding the relationships between software metrics.