Optimising conceptual data models through profiling in object databases

Abstract

Agile methods promote iterative development with short cycles, where user feedback from the previous iteration is used to refactor and improve the current version. For information systems development, we propose to extend this feedback loop by using database profiling information to propose adaptations to the conceptual model to improve performance. For every software release, our database profiler identifies and analyses navigational access patterns, and proposes model optimisations based on data characteristics, access patterns and a cost-benefit model. The proposed model optimisations are based on common database and data model refactoring patterns. The database profiler has been implemented as part of an open-source object database and integrated into an existing agile development environment, where the model optimisations are presented as part of the IDE. We evaluate our approach based on an example of agile development of a research publication system. © Springer-Verlag 2013.