DocumentCode
815888
Title
An entropy-based measure of software complexity
Author
Harrison, Warren
Author_Institution
PSU Center for Software Quality Res., Portland State Univ., OR, USA
Volume
18
Issue
11
fYear
1992
fDate
11/1/1992 12:00:00 AM
Firstpage
1025
Lastpage
1029
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;
fLanguage
English
Journal_Title
Software Engineering, IEEE Transactions on
Publisher
ieee
ISSN
0098-5589
Type
jour
DOI
10.1109/32.177371
Filename
177371
Link To Document