Search-based improvement of subsystem decompositions

The subsystem decomposition of a software system degrades gradually during its lifetime and therefore it gets harder and harder to maintain. As a result this decomposition needs to be reconditioned from time to time. The problem is to determine a suitable subsystem decomposition that can be used as a basis for future maintenance tasks. This paper describes a new methodology that computes such a subsystem decomposition by optimizing metrics and heuristics of good subsystem design. The main idea is to treat this task as a search problem and to solve it using a genetic algorithm.

[1]  Robert C. Martin.  Agile Software Development, Principles, Patterns, and Practices , 2002 .

[2]  Nicolas Anquetil,et al.  Experiments with clustering as a software remodularization method , 1999, Sixth Working Conference on Reverse Engineering (Cat. No.PR00303).

[3]  Derek Rayside,et al.  The effect of call graph construction algorithms for object-oriented programs on automatic clustering , 2000, Proceedings IWPC 2000. 8th International Workshop on Program Comprehension.

[4]  Emanuel Falkenauer,et al.  Genetic Algorithms and Grouping Problems , 1998 .

[5]  Emden R. Gansner,et al.  Bunch: a clustering tool for the recovery and maintenance of software system structures , 1999, Proceedings IEEE International Conference on Software Maintenance - 1999 (ICSM'99). 'Software Maintenance for Business Change' (Cat. No.99CB36360).

[6]  Ralph Johnson,et al.  design patterns elements of reusable object oriented software , 2019 .

[7]  Volker Kuttruff,et al.  Source-to-Source Transformation in the Large , 2003, JMLC.

[8]  Oliver Ciupke,et al.  Automatic detection of design problems in object-oriented reengineering , 1999, Proceedings of Technology of Object-Oriented Languages and Systems - TOOLS 30 (Cat. No.PR00278).

[9]  Juraj Hromkovic,et al.  Algorithmics for Hard Problems , 2002, Texts in Theoretical Computer Science An EATCS Series.

[10]  Spiros Mancoridis,et al.  Automatic clustering of software systems using a genetic algorithm , 1999, STEP '99. Proceedings Ninth International Workshop Software Technology and Engineering Practice.

[11]  Charles T. Zahn,et al.  Graph-Theoretical Methods for Detecting and Describing Gestalt Clusters , 1971, IEEE Transactions on Computers.

[12]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[13]  Richard C. Holt,et al.  The Orphan Adoption problem in architecture maintenance , 1997, Proceedings of the Fourth Working Conference on Reverse Engineering.

[14]  Mircea Trifu,et al.  Architecture-aware adaptive clustering of OO systems , 2004, Eighth European Conference on Software Maintenance and Reengineering, 2004. CSMR 2004. Proceedings..

[15]  Richard C. Holt,et al.  Software botryology. Automatic clustering of software systems , 1998, Proceedings Ninth International Workshop on Database and Expert Systems Applications (Cat. No.98EX130).

[16]  David Lorge Parnas,et al.  Software aging , 1994, Proceedings of 16th International Conference on Software Engineering.

[17]  Emden R. Gansner,et al.  Using automatic clustering to produce high-level system organizations of source code , 1998, Proceedings. 6th International Workshop on Program Comprehension. IWPC'98 (Cat. No.98TB100242).

[18]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[19]  T. A. Wiggerts,et al.  Using clustering algorithms in legacy systems remodularization , 1997, Proceedings of the Fourth Working Conference on Reverse Engineering.