Sun 23 - Fri 28 October 2022 Montréal, Canada
Fri 28 Oct 2022 10:30 - 11:00 at A-3502.1 - Most Influential PapersTechnical Track

Model-based robustness testing requires precise and complete behavioral, robustness modeling. For example, state machines can be used to model software behavior when hardware (e.g., sensors) breaks down and be fed to a tool to automate test case generation. But robustness behavior is a crosscutting behavior and, if modeled directly, often results in large, complex state machines. These in practice tend to be error prone and difficult to read and understand. As a result, modeling robustness behavior in this way is not scalable for complex industrial systems. To overcome these problems, aspect-oriented modeling (AOM) can be employed to model robustness behavior as aspects in the form of state machines specifically designed to model robustness behavior. In this paper, we present a RobUstness Modeling Methodology (RUMM) that allows modeling robustness behavior as aspects. Our goal is to have a complete and practical methodology that covers all features of state machines and aspect concepts necessary for model-based robustness testing. At the core of RUMM is a UML profile (AspectSM) that allows modeling UML state machine aspects as UML state machines (aspect state machines). Such an approach, relying on a standard and using the target notation as the basis to model the aspects themselves, is expected to make the practical adoption of aspect modeling easier in industrial contexts. We have used AspectSM to model the crosscutting robustness behavior of a videoconferencing system and discuss the benefits of doing so in terms of reduced modeling effort and improved readability.