Biological system modeling is an iterative process where uncertainties may arise, especially in the early stages of the modeling. Static analysis tools are needed during each stage of the modeling to help modelers detect unexpected behaviors early by automatically inferring properties about the model. However, the rule-based modeling language Kappa and its static analysis tool KaSa currently lack support for incomplete models.
In this work, we extend Kappa to support incomplete models, where some rules are considered or not considered depending on the value of some boolean parameters. We also generalize the current reachability analysis of the static analyzer KaSa to these parametric models, establishing relationships between properties and parameter values. Finally, we implement and evaluate our approach on example models.
