A comparison of data flow path selection criteria
ICSE '85 Proceedings of the 8th international conference on Software engineering
The Psychology of How Novices Learn Computer Programming
ACM Computing Surveys (CSUR)
Control flow and data structure documentation: two experiments
Communications of the ACM
Studying programmer behavior experimentally: the problems of proper methodology
Communications of the ACM
A psychology of learning BASIC
Communications of the ACM
Elements of Software Science (Operating and programming systems series)
Elements of Software Science (Operating and programming systems series)
ICSE '81 Proceedings of the 5th international conference on Software engineering
Third time charm: Stronger prediction of programmer performance by software complexity metrics
ICSE '79 Proceedings of the 4th international conference on Software engineering
Enhanced effort estimation by extending basic programming models to include modularity factors
Enhanced effort estimation by extending basic programming models to include modularity factors
A complexity measure based on nesting level
ACM SIGPLAN Notices
The impact of programming styles on debugging efficiency
ACM SIGSOFT Software Engineering Notes
Software psychology: Human factors in computer and information systems (Winthrop computer systems series)
A Mathematical Theory of Communication
A Mathematical Theory of Communication
Recent advances in software measurement (abstract and references for talk)
ICSE '90 Proceedings of the 12th international conference on Software engineering
Properties of Control-Flow Complexity Measures
IEEE Transactions on Software Engineering
An Entropy-Based Measure of Software Complexity
IEEE Transactions on Software Engineering - Special issue on software measurement principles, techniques, and environments
Measures of syntactic complexity for modeling behavioral VHDL
DAC '95 Proceedings of the 32nd annual ACM/IEEE Design Automation Conference
The mathematical validity of software metrics
ACM SIGSOFT Software Engineering Notes
Proceedings of the 2002 ACM symposium on Applied computing
The measurement of software design quality
Annals of Software Engineering
Empirical Assessment of a Software Metric: The Information Content of Operators
Software Quality Control
Journal of Software Maintenance: Research and Practice
Computers and Operations Research
Towards a Semantic Metrics Suite for Object-Oriented Design
TOOLS '00 Proceedings of the Technology of Object-Oriented Languages and Systems (TOOLS 34'00)
Entropies as Measures of Software Information
ICSM '01 Proceedings of the IEEE International Conference on Software Maintenance (ICSM'01)
Software metrics, information and entropy
Practicing software engineering in the 21st century
Spatial Complexity Metrics: An Investigation of Utility
IEEE Transactions on Software Engineering
Measuring the Complexity of a UML Component Specification
QSIC '05 Proceedings of the Fifth International Conference on Quality Software
A complexity measure for UML component-based system specification
Software—Practice & Experience
Entropy metric for XML DTD documents
ACM SIGSOFT Software Engineering Notes
Code complexity metrics for mobile agents implemented with aspect/J™
CEEMAS'03 Proceedings of the 3rd Central and Eastern European conference on Multi-agent systems
The structured complexity of object-oriented programs
Mathematical and Computer Modelling: An International Journal
Complexity metrics for cascading style sheets
ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part IV
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A study of the predictive value of a variety of syntax-based problem complexity measures is reported. Experimentation with variants of chunk-oriented measures showed that one should judiciously select measurable software attributes as proper indicators of what one wishes to predict, rather than hoping for a single, all-purpose complexity measure. The authors have shown that it is possible for particular complexity measures or other factors to serve as good predictors of some properties of program but not for others. For example, a good predictor of construction time will not necessarily correlate well with the number of error occurrences. M.H. Halstead's (1977) efforts measure (E) was found to be a better predictor that the two nonchunk measures evaluated, namely, T.J. McCabe's (1976) V(G) and lines of code, but at least one chunk measure predicted better than E in every case.