Open Analytic Runtime (OAR) Models embed analysis algorithms into runtime architectural models, thus integrating the model and its analytic interpretations. Such an integration is critical for Cyber-Physical Systems (CPS) when model parts are independently developed by different teams as it is the case in multi-tier industries, e.g. avionics and automotive. Analysis algorithms play a central role augmenting the designer's capacity to automatically verify properties of interest in systems at the scale and complexity required by these industries. Unfortunately, the verification results are valid only if the assumptions of the different analysis algorithms (analytic assumptions) are consistent with each other. This paper presents our work on the automatic verification of one important class of analytic assumptions in OAR models: resource allocation assumptions. These assumptions are modeled as Resource Allocation (RA) contracts. RA contract constructs include not only the typical assumes and guarantees but also runtime facts and impli- cations. Finally, we automatically determine the correct sequence of execution of the analysis algorithms based on the contract input/output dependencies described in our models. Together these characteristics enable the automatic assumption verification that preserves the scalability of analytic models. We illustrate our approach using an example model with analysis algorithms for security, schedulability, and energy efficiency.