S/C: a Software Size/Complexity Measure

Abstract

A new software structural complexity metric is proposed which is a simple, yet powerful, extension of the normal lines of code count. This measure is shown to account for the differences in complexity of program statements in high-order languages and is useful in assessing control complexity of source programs objectively when the source code is available. The proposed measure also satisfies the seventh axiom of Weyuker's software complexity measures (complexity is dependent on permutation of source statements). The measure has the potential (not fully evaluated here) for use in assessing the effort related to understanding software for software maintenance, debugging and generalization. In our pilot project, we found that the time taken to trace artificial bugs introduced in programs is explained better by SIC counts than by lines of code counts.