Software metrics and measurement principles
ACM SIGSOFT Software Engineering Notes
A validation of software metrics using many metrics and two resources
ICSE '85 Proceedings of the 8th international conference on Software engineering
ACM '85 Proceedings of the 1985 ACM annual conference on The range of computing : mid-80's perspective: mid-80's perspective
Problems with software complexity measurement
CSC '85 Proceedings of the 1985 ACM thirteenth annual conference on Computer Science
IEEE Transactions on Knowledge and Data Engineering
Program complexity measure for software development management
ICSE '81 Proceedings of the 5th international conference on Software engineering
Are current approaches sufficient for measuring software quality?
Proceedings of the software quality assurance workshop on Functional and performance issues
Prediction models for cyclomatic complexity
ACM SIGPLAN Notices
Software metrics: an introduction and annotated bibliography
ACM SIGSOFT Software Engineering Notes
A comparison of program complexity prediction models
ACM SIGSOFT Software Engineering Notes
On the complexity of measuring software complexity
AFIPS '81 Proceedings of the May 4-7, 1981, national computer conference
Taking the measure of program complexity
AFIPS '81 Proceedings of the May 4-7, 1981, national computer conference
Measuring program complexity in a COBOL environment
AFIPS '80 Proceedings of the May 19-22, 1980, national computer conference
Entropy metrics for software design evaluation
Journal of Systems and Software
Journal of Systems and Software
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A frequently stated objective of structured programming is to control program complexity. However, since the notion of complexity is not well under-stood and the existing techniques for measuring complexity are crude, it is difficult to determine if indeed structured programming can achieve this objective. The purpose of this paper is two-fold: to discuss the probable sources of complexity in a well-structured program to present a methodology for measuring and controlling complexity in a well-structured program.