Partial models: Towards modeling and reasoning with uncertainty

Abstract

Models are good at expressing information about software but not as good at expressing modelers' uncertainty about it. The highly incremental and iterative nature of software development nonetheless requires the ability to express uncertainty and reason with models containing it. In this paper, we build on our earlier work on expressing uncertainty using partial models, by elaborating an approach to reasoning with such models. We evaluate our approach by experimentally comparing it to traditional strategies for dealing with uncertainty as well as by conducting a case study using open source software. We conclude that we are able to reap the benefits of well-managed uncertainty while incurring minimal additional cost.