A style analysis of C programs
Communications of the ACM - Special section on computer architecture
Debugging Effort Estimation Using Software Metricsv
IEEE Transactions on Software Engineering
A proposal for measuring the structural complexity of programs
Journal of Systems and Software
An empirical study of the use of the GOTO statement
Journal of Systems and Software
Techniques for application software maintenance
Information and Software Technology
Quantitative models of cohesion and coupling in software
Selected papers of the sixth annual Oregon workshop on Software metrics
A Validation of Object-Oriented Design Metrics as Quality Indicators
IEEE Transactions on Software Engineering
Effect of software structure attributes on software development productivity
Journal of Systems and Software
Status Report on Software Measurement
IEEE Software
A Metrics Suite for Object Oriented Design
IEEE Transactions on Software Engineering
Software Structure Metrics Based on Information Flow
IEEE Transactions on Software Engineering
Take a walk and cluster genes: a TSP-based approach to optimal rearrangement clustering
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Rearrangement Clustering: Pitfalls, Remedies, and Applications
The Journal of Machine Learning Research
PIXSAR: incremental reclustering of augmented XML trees
Proceedings of the 10th ACM workshop on Web information and data management
iPIXSAR: incremental clustering of indexed XML data
Proceedings of the 2009 EDBT/ICDT Workshops
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Years of programming experience has convinced us that the physical structure of a program, such as the locations of the program's components, their calls, and the depth of nested calls, is important in determining how effective and efficient the program can be debugged and maintained. This paper introduces a new class of physical metrics, known as locality metric, that measures the relative positions of components in a program listing and reveals useful attributes that may affect programmer productivity. The placement of the components can be determined by a simple algorithm that is of polynomial time complexity. The paper compares the performance of the algorithm with that of an exhaustive search approach and also reports various characteristics of the locality metric based on the collected statistical data. The performance shows the feasibility of the algorithm and closeness of its output to the optimal result found by the exhaustive approach.