A Cognitive Complexity Metric Based on Category Learning
ICCI '03 Proceedings of the 2nd IEEE International Conference on Cognitive Informatics
A brief survey of program slicing
ACM SIGSOFT Software Engineering Notes
Spatial Complexity Metrics: An Investigation of Utility
IEEE Transactions on Software Engineering
Fine-grain analysis of common coupling and its application to a Linux case study
Journal of Systems and Software
An empirical study of rules for well-formed identifiers: Research Articles
Journal of Software Maintenance and Evolution: Research and Practice - Source Code Analysis and Manipulation (SCAM 2006)
Quantifying identifier quality: an analysis of trends
Empirical Software Engineering
Slicing obfuscations: design, correctness, and evaluation
Proceedings of the 2007 ACM workshop on Digital Rights Management
Identifier length and limited programmer memory
Science of Computer Programming
Object-Oriented Inheritance Metrics: Cognitive Complexity Perspective
RSKT '09 Proceedings of the 4th International Conference on Rough Sets and Knowledge Technology
Object-Oriented Inheritance Metrics in the Context of Cognitive Complexity
Fundamenta Informaticae - Knowledge Technology
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Achieving and maintaining high software quality is most dependent on how easily the software engineer least familiar with the system can understand the system's code. Understanding attributes of cognitive processes can lead to new software metrics that allow the prediction ofhuman performance in software development and for assessing and improving the understandability of text and code. In this research we present novel metrics based on current understanding of short-term memory performance, to predict the location of high frequenciesof errors and to evaluate the quality of a software system. We further enhance these metrics by applying static and dynamic program slicing to provide programmers with additional guidance during software inspection and maintenance efforts.