Testing of a software system is a resource-consuming activity that requires high-level expert knowledge. Methods based on knowledge representation and reasoning can alleviate this problem. This paper presents an approach to enhance the automation of the testing process using ontologies and inference rules. The approach takes software requirements specifications written in structured text documents as input and produces the output, i.e. test scripts. The approach makes use of ontologies to deal with the knowledge embodied in requirements specifications and to represent the desired structure of test cases, as well as makes use of a set of inference rules to represent strategies for deriving test cases. The implementation of the approach, in the context of an industrial case, proves the validity of the overall approach.