Interactive Programmatic Modeling

Modeling and computational analyses are fundamental activities within science and engineering. Analysis activities can take various forms, such as simulation of executable models, formal verification of model properties, or inference of hidden model variables. Traditionally, tools for modeling and analysis have similar workflows: (i) a user designs a textual or graphical model or the model is inferred from data, (ii) a tool performs computational analyses on the model, and (iii) a visualization tool displays the resulting data. This article identifies three inherent problems with the traditional approach: the recomputation problem, the variable inspection problem, and the model expressiveness problem. As a solution, we propose a conceptual framework called Interactive Programmatic Modeling. We formalize the interface of the framework and illustrate how it can be used in two different domains: equation-based modeling and probabilistic programming.