Automatic Robustness Assessment of DDS-Compliant Middleware

Abstract

The next generation of critical systems requires an efficient, scalable and robust data dissemination infrastructure. Middleware solutions compliant with the novel OMG standard, called Data Distribution Service (DDS), are being traditionally used for architecting large-scale systems, because they well meet the requirements of scalability, seamless decoupling and fault tolerance. Due to such features, industrial practitioners are enforcing the adoption of such middleware solutions also within the context of critical systems. However, these systems pose serious dependability requirements, which in turn demand DDS compliant products also to realize reliable data dissemination in different and heterogeneous contexts. Hence, assessing the supported reliability degree and proposing improvement strategies becomes crucial and requires a clear understanding of DDS compliant middleware failing behavior. This paper illustrates an innovative tool to automatically evaluate the robustness of DDS-compliant middleware based on a fault injection technique. Specifically, experiments have been conducted on an actual implementation of the DDS standard, by means of injecting a set of proper invalid inputs through its API and analyzing the achieved outcomes.