Experimentation in software engineering: an introduction
Experimentation in software engineering: an introduction
A State-of-the-Art Survey on Software Merging
IEEE Transactions on Software Engineering
Aspect-Oriented Analysis and Design
Aspect-Oriented Analysis and Design
Semantic-based weaving of scenarios
Proceedings of the 5th international conference on Aspect-oriented software development
Effects of defects in UML models: an experimental investigation
Proceedings of the 28th international conference on Software engineering
Model-driven Development of Complex Software: A Research Roadmap
FOSE '07 2007 Future of Software Engineering
Safe composition of product lines
GPCE '07 Proceedings of the 6th international conference on Generative programming and component engineering
Synthesizing hierarchical state machines from expressive scenario descriptions
ACM Transactions on Software Engineering and Methodology (TOSEM)
Assessing the impact of aspects on model composition effort
Proceedings of the 9th International Conference on Aspect-Oriented Software Development
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The lack of empirical knowledge about the effects of model composition techniques on developers' effort is the key impairment for their widespread adoption in practice. This problem applies to both existing categories of model composition techniques, i.e. specification-based (e.g. Epsilon) and heuristic-based (e.g. IBM RSA) techniques. This paper reports on a controlled experiment that investigates the effort to: (1) apply both categories of model composition techniques, and (2) detect and resolve inconsistencies in the output composed models. The techniques are investigated in 144 evolution scenarios, where 2304 compositions of elements of class diagrams were produced. The results suggest that: (1) the employed heuristic-based techniques require less effort to produce the intended model than the chosen specification-based technique, (2) the correctness of the output composed models generated by the techniques is not significantly different, and (3) the use of manual heuristics for model composition outperforms their automated counterparts.