Dynamic code coverage metrics: a lognormal perspective

The logical interrelationship between different code coverage types has been well studied, but less so their evolution through time or test. We study the dynamic relationship of four coverage types, namely, block, decision, c-use and p-use by comparing their growth using empirical coverage data generated from extensive testing of a software application with 35 KLOC of code. Our results indicate that as testing increases, the growth trends for each coverage type are surprisingly similar. Not only is each trend consistent with an underlying lognormal distribution of event rate, but also the parameters of the fitted lognormal distributions are closely related. Within the limits of the data, we find quantitative relations between the four coverage types. The paper thus takes a significant step in linking concepts from prior studies of software test sufficiency, test efficiency, and reliability in the context of software execution