Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Design patterns: elements of reusable object-oriented software
Design patterns: elements of reusable object-oriented software
Software architecture: perspectives on an emerging discipline
Software architecture: perspectives on an emerging discipline
A Metrics Suite for Object Oriented Design
IEEE Transactions on Software Engineering
A New Representation And Crossover Operator For Search-based Optimization Of Software Modularization
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Can Metrics Help to Bridge the Gap Between the Improvement of OO Design Quality and Its Automation?
ICSM '00 Proceedings of the International Conference on Software Maintenance (ICSM'00)
Search-based improvement of subsystem decompositions
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Pareto optimal search based refactoring at the design level
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Getting the most from search-based refactoring
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Multi-objective genetic synthesis of software architecture
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Multi-level automated refactoring using design exploration
SSBSE'11 Proceedings of the Third international conference on Search based software engineering
Survey: A survey on search-based software design
Computer Science Review
Search-based software engineering: Trends, techniques and applications
ACM Computing Surveys (CSUR)
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Design of software architecture is intellectually one of the most demanding tasks in software engineering. This paper proposes an approach to automatically synthesize software architecture using genetic algorithms. The technique applies architectural patterns for mutations and quality metrics for evaluation, producing a proposal for a software architecture on the basis of functional requirements given as a graph of functional responsibilities. Two quality attributes, modifiability and efficiency, are considered. The behavior of the genetic synthesis process is analyzed with respect to quality improve ment speed, the effect of dynamic mutation, and the effect of quality attribute prioritization. Our tests show that it is possible to genetically synthesize architectures that achieve a high fitness value early on.