An improved algorithm for identifying objects in code
Software—Practice & Experience
Assessing modular structure of legacy code based on mathematical concept analysis
ICSE '97 Proceedings of the 19th international conference on Software engineering
An intelligent tool for re-engineering software modularity
ICSE '91 Proceedings of the 13th international conference on Software engineering
Identifying objects using cluster and concept analysis
Proceedings of the 21st international conference on Software engineering
A comparison of abstract data types and objects recovery techniques
Science of Computer Programming - Special issue on WCRE 97
A Metric-Based Approach to Detect Abstract Data Types and State Encapsulations
Automated Software Engineering
A Concept Formation Based Approach to Object Identification in Procedural Code
Automated Software Engineering
Identifying modules via concept analysis
ICSM '97 Proceedings of the International Conference on Software Maintenance
Software Botryology, Automatic Clustering of Software Systems
DEXA '98 Proceedings of the 9th International Workshop on Database and Expert Systems Applications
Using Clustering Algorithms in Legacy Systems Remodularization
WCRE '97 Proceedings of the Fourth Working Conference on Reverse Engineering (WCRE '97)
MoJo: A Distance Metric for Software Clusterings
WCRE '99 Proceedings of the Sixth Working Conference on Reverse Engineering
On the Stability of Software Clustering Algorithms
IWPC '00 Proceedings of the 8th International Workshop on Program Comprehension
Using concept analysis to detect co-change patterns
Ninth international workshop on Principles of software evolution: in conjunction with the 6th ESEC/FSE joint meeting
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Software Clustering and Concept Analysis are two types of technique that can be used to determine the structure of a software system. This position paper proposes the use of such techniques to aid the study of software evolution. Basic Software Clustering and Concept Analysis techniques are described. By applying these techniques to different versions of a software system, it is possible that evolutionary trends over the lifetime of the system could be discovered. Work is proposed that will attempt to establish whether this is the case.