Automated Test Generation for Access Control Policies via Change-Impact Analysis

Access control policies are increasingly written in specification lan-guages such as XACML. A dedicated software component called a Policy Decision Point (PDP) receives access requests, evaluates requests against specified policies, and returns responses to inform whether access should be granted. To increase confidence in the correctness of specified policies, policy developers can conduct policy testing to probe the PDP with some typical test inputs (in the form of requests) and check test outputs (in the form of re-sponses) against expected ones. Unfortunately, manual test genera-tion is tedious and manually generated tests are often not sufficient to exercise various policy behaviors. In this paper we present an efficient test generation approach and its supporting tool called Targen. We model the policy under test as a tree, perform a depth-first traversal specifically targeting eac