Abstract
Software complexity metrics attempt to objectively measure the difficulty involved in creating and maintaining a program. This experiment will compare five complexity metrics as measures for reading comprehension of programs. The metrics compared are Halstead's effort, McCabe's cyclomatic, Oviedo's program complexity, Gilb's logical complexity, and data dependency tree count. The metrics will be applied to independent groups of four functionally equivalent PL/I programs. These results will be compared to the subjective ranking of a control group of competent programmers after agreement among the experts has been determined. These results will be compared using the Friedman two-way analysis of variance by ranks and a multiple comparison procedure. The Friedman two-way analysis of variance by ranks determines if a significant difference exists between metrics. Once this has been established the multiple comparison procedure will be used to determine how the metrics differ.
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