Code coverage is usually used as a measurement of testing quality and as adequacy criterion. Unfortunately, code coverage is very sensitive to modifications of the code structure, and, therefore, we can achieve the same degree of coverage with different testing effort by writing the same program in syntactically different ways. For this reason, code coverage can provide the tester with misleading information. In order to understand how a testing criterion is affected by code structure modifications, we have introduced a way to measure the sensitivity of coverage to code changes by means of code-to-code transformations. However the manual execution of the robustness analysis is tedious, time consuming and error prone. In order to solve these issues we present AURORA, a tool that automates the robustness analysis process and leverages the capabilities offered from several existing tools. AURORA has an extendible architecture that concretely supports the tester in the execution of the robustness analysis. Due to this extendible architecture, each user can personalize the robustness analysis to his/her needs. AURORA allows the user to add new transformations by using TXL, which is a programming language specifically designed to support source transformation tasks. It performs the coverage evaluation by using existing code coverage tools and is based on the use of the JUnit framework.