Search

Experimenting with futuristic computer workstation design and specifically tailored application models can yield useful insights and result in exciting ways to increase efficiency, effectiveness, and satisfaction for computer users. Designing and building a computer workstation that can track a user’s gaze; sense proximity to the touch surface; and support multi-touch, face recognition etc meant overcoming some unique technological challenges. Coupled with extensions to commonly used applications to report user interactions in a meaningful way, the workstation will allow the development of a rich contextual user model that is accurate enough to enable benefits, such as contextual filtering, task automation, contextual auto-fill, and improved understanding of team collaborations. SRI’s bRIGHT workstation was designed and built to explore these research avenues and investigate how such a context model can be built, identify the key implications in designing an application model that best serves these goals, and discover other related factors. This paper conjectures future research that would support the development of a collaborative context model that could leverage similar benefits for groups of users.

Requirements are informal and semi-formal descriptions of the expected behavior of a complex system from the viewpoints of its stakeholders customers, users, operators, designers, and engineers. However, for the purpose of design, testing, and verification for critical systems, we can transform requirements into formal models that can be analyzed automatically. ARSENAL is a framework and methodology for systematically transforming natural language NL requirements into analyzable formal models and logic specifications. These models can be analyzed for consistency and implementability. The ARSENAL methodology is specialized to individual domains, but the approach is general enough to be adapted to new domains.

This paper is a tribute to Jose Meseguer, from the rest of us in the Maude team, reviewing the past, the present, and the future of the language and system with which we have been working for around two decades under his leadership. After reviewing the origins and the language’s main features, we present the latest additions to the language and some features currently under development. This paper is not an introduction to Maude, and some familiarity with it and with rewriting logic are indeed assumed.

We present a new procedure for testing satisfiability (over the reals) of a conjunction of polynomial equations. There are three possible return values for our procedure: it either returns a model for the input formula, or it says that the input is unsatisfiable, or it fails because the applicability condition for the procedure, called the eigen-condition, is violated. For the class of constraints where the eigen-condition holds, our procedure is a decision procedure. We describe satisfiability-preserving transformations that can potentially convert problems into a form where eigen-condition holds. We experimentally evaluate the procedure and discuss applicability.