A major advantage in using a case-based approach to developing knowledge-based systems is that it can be applied to problems where a strong domain theory may be difficult to determine. However the development of case-based reasoning (CBR) systems that set out to support a sophisticated case adaptation process does require a strong domain model. The Derivational Analogy (DA) approach to CBR is a case in point. In DA the case representation contains a trace of the reasoning process involved in producing the solution for that case. In the adaptation process this reasoning trace is reinstantiated in the context of the new target case; this requires a strong domain model and the encoding of problem solving knowledge. In this paper we analyse this issue using as an example a CBR system called CoBRA that assists with the modelling tasks in numerical simulation.