Compositional modeling: finding the right model for the job
Artificial Intelligence - Special issue: Qualitative reasoning about physical systems II
Efficient compositional modeling for generating causal explanations
Artificial Intelligence
Components and generative programming (invited paper)
ESEC/FSE-7 Proceedings of the 7th European software engineering conference held jointly with the 7th ACM SIGSOFT international symposium on Foundations of software engineering
Simulation modeling with event graphs
Communications of the ACM
ACM SIGPLAN Notices
Optimization and response surfaces: an optimization-based multi-resolution simulation methodology
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
The computational complexity of component selection in simulation reuse
WSC '05 Proceedings of the 37th conference on Winter simulation
Simulation-specific characteristics and software reuse
WSC '05 Proceedings of the 37th conference on Winter simulation
Using flexible points in a developing simulation of selective dissolution in alloys
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Agile optimization for coercion
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
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Dynamic data-driven application systems (DDDAS) integrate computer simulations with experimental observations to study phenomena with greater speed and accuracy than could be achieved by either experimentation or simulation alone. One of the key challenges behind DDDAS is automatically adapting simulations when experimental data indicates that a simulation must change. Coercion is a semi-automated simulation adaptation approach that can be automated further if elements of the simulation called flexible points are described in advance. In this paper, we use a number of DDDAS adaptation examples to identify the information that needs to be captured about flexible points in order to support coercion.