Date of Graduation


Document Type


Degree Type



Statler College of Engineering and Mineral Resources


Lane Department of Computer Science and Electrical Engineering

Committee Chair

Hany H. Ammar.


Risk is the possibility of suffering loss. Risks identified during the early stages of software development are easier and cheaper to handle by making changes to the software architecture. This thesis presents methodologies to assess software risk using Unified Modeling Language (UML) specifications of the software from the early design stages. We present methodologies to assess two types of software risk: Requirements-based risk and Performance-based risk. In assessing requirements-based risk, each requirement is mapped to a specific operational scenario in UML. The risk factor of a scenario in a failure mode is obtained by combining the probability of failure of the scenario and the severity of the failure. For the performance-based risk analysis, we use UML diagrams with performance related annotations, build a software execution model for each scenario and then map it to a system execution model using the deployment information. For estimating the performance-based failures of each scenario we use an asymptotic bounding analysis. The methodologies are applied on various case studies.