Title :
An entropy-based measure of software complexity
Author :
Harrison, Warren
Author_Institution :
PSU Center for Software Quality Res., Portland State Univ., OR, USA
fDate :
11/1/1992 12:00:00 AM
Abstract :
It is proposed that the complexity of a program is inversely proportional to the average information content of its operators. An empirical probability distribution of the operators occurring in a program is constructed, and the classical entropy calculation is applied. The performance of the resulting metric is assessed in the analysis of two commercial applications totaling well over 130000 lines of code. The results indicate that the new metric does a good job of associating modules with their error spans (averaging number of tokens between error occurrences)
Keywords :
probability; software metrics; average information content; classical entropy calculation; empirical probability distribution; entropy-based measure; performance; software complexity; Application software; Computer errors; Entropy; Information theory; Performance analysis; Probability distribution; Programming profession; Software measurement; Software quality; Software testing;
Journal_Title :
Software Engineering, IEEE Transactions on
