AN ENTROPY-BASED MEASURE OF SOFTWARE COMPLEXITY

被引：81

作者：

HARRISON, W

机构：

[1] PSU Center for Software Quality Research, Portland State University, Portland, OR

来源：

IEEE TRANSACTIONS ON SOFTWARE ENGINEERING | 1992年 / 18卷 / 11期

关键词：

INFORMATION THEORY; SOFTWARE METRICS; SOFTWARE PROJECT MANAGEMENT; SOFTWARE QUALITY;

D O I：

10.1109/32.177371

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

Many different methods have been suggested for measuring "Software Complexity." In this paper, 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 applied: H = - SIGMAp(i) log2p(i). The performance of this metric is assessed in the analysis of two commercial applications totalling well over 130 000 lines of code. The results suggest the new metric does a good job of associating modules with their error spans (average number of tokens between error occurrences).

引用

页码：1025 / 1029

页数：5

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