Code-Imp: a tool for automated search-based refactoring
Proceedings of the 4th Workshop on Refactoring Tools
Multi-level automated refactoring using design exploration
SSBSE'11 Proceedings of the Third international conference on Search based software engineering
Proceedings of the 5th India Software Engineering Conference
Search based software engineering: techniques, taxonomy, tutorial
Empirical Software Engineering and Verification
Proceedings of the 27th IEEE/ACM International Conference on Automated Software Engineering
Putting the developer in-the-loop: an interactive GA for software re-modularization
SSBSE'12 Proceedings of the 4th international conference on Search Based Software Engineering
A concept for an interactive search-based software testing system
SSBSE'12 Proceedings of the 4th international conference on Search Based Software Engineering
A comparison of two memetic algorithms for software class modelling
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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Although much evidence exists to suggest that early life cycle software engineering design is a difficult task for software engineers to perform, current computational tool support for software engineers is limited. To address this limitation, interactive search-based approaches using evolutionary computation and software agents are investigated in experimental upstream design episodes for two example design domains. Results show that interactive evolutionary search, supported by software agents, appears highly promising. As an open system, search is steered jointly by designer preferences and software agents. Directly traceable to the design problem domain, a mass of useful and interesting class designs is arrived at which may be visualized by the designer with quantitative measures of structural integrity, such as design coupling and class cohesion. The class designs are found to be of equivalent or better coupling and cohesion when compared to a manual class design for the example design domains, and by exploiting concurrent execution, the runtime performance of the software agents is highly favorable.