Abstract:
This thesis proposes a solution to test calculation engines in financial services
applications such as banking, mortgage, insurance, and trading. Calculation engines form
the heart of financial applications, as the results are very sensitive to the business and can
cause severe damage if wrong. But controllability and observability of these calculations
are low. In order to test these calculations, more robust and sophisticated methods are
required. In this thesis, input space partitioning, along with automation, were applied with
the help of tools. Case studies were conducted to validate the effectiveness of this
approach. Finally, a framework is recommended to test the calculation engines.
