Justyna Zander

From U2TP models to executable tests with TTCN-3 - an approach to model driven testing -

The approach towards system engineering according to Model-Driven Architectures (MDA) with code generation derived from model implies also an increased need for research on automation of the test generation process. This paper presents an approach to derive executable tests from UML 2.0 Testing Profile diagrams automatically. In particular, an approach to derive executable tests within the Testing and Test Control Notation (TTCN-3) is discussed. The transformation rules between the source U2TP meta-model to the target TTCN-3 meta-model are given.

Cyber-physical systems challenges: a needs analysis for collaborating embedded software systems

Embedding computing power in a physical environment has provided the functional flexibility and performance necessary in modern products such as automobiles, aircraft, smartphones, and more. As product features came to increasingly rely on software, a network infrastructure helped factor out common hardware and offered sharing functionality for further innovation. A logical consequence was the need for system integration. Even in the case of a single original end manufacturer who is responsible for the final product, system integration is quite a challenge. More recently, there have been systems coming online that must perform system integration even after deployment—that is, during operation. This has given rise to the cyber-physical systems (CPS) paradigm. In this paper, select key enablers for a new type of system integration are discussed. The needs and challenges for designing and operating CPS are identified along with corresponding technologies to address the challenges and their potential impact. The intent is to contribute to a model-based research agenda in terms of design methods, implementation technologies, and organization challenges necessary to bring the next-generation systems online.

A Heterogeneous Fleet of Vehicles for Automated Humanitarian Missions

An automated emergency response system and an experimental framework for its design and validation are presented here. The system consists of a high-level mission optimization and a fleet of heterogeneous autonomous vehicles. The fleet includes ground vehicles for setting up local stations, fixed-wing aircraft for assessing infrastructure damage and performing surveillance, and rotorcraft for delivering emergency supplies. Internet technology provides a unifying environment for the vehicles, optimization module, operators, and emergency responders with support for computational integration in cyberspace.

Towards Computational Hybrid System Semantics for Time-Based Block Diagrams

Abstract At the core of Model-Based Design, computational models have caused an autocatalytic trend to use computation in design by unlocking the potential of model transformations. Precisely specifying a computational transformation requires well-defined semantics of the source and target representations. In this regard, continuous-time behavior is an essential aspect of time-based block diagrams that is typically approximated by numerical integration. The corresponding theory, however, is mostly concerned with local error and the mathematical semantics of long time behavior fails to be sufficiently precise from a computational perspective. In this work, first a computational semantics is developed based on a multi-stage variablestep solver. Next, the computational semantics of the discrete and continuous parts of hybrid systems and their interaction are formalized in a unifying framework. The framework exploits a successful functional approach to defining discrete-time and discrete-event behavior established in other work. Unification is then achieved by developing a computational representation of the continuous-time behavior as pure functions on streams.

Computation for Humanity: Information Technology to Advance Society

The exponential progress and accessibility of computing has vastly increased data flows and revolutionized the practice of science, engineering, and communication. Computing plays a critical role in advancing research across almost every scientific discipline. Computation for Humanity: Information Technology to Advance Society is a guide for the creation of services, products, and tools that facilitate, support, and enhance progress of humanity toward more sustainable life. This book: Provides a deep understanding of the practical applications of computation to solve human-machine problems Delivers insight into theoretical approaches in an accessible manner Provides a comprehensive overview of computational science and engineering applications in selected disciplines Crosses the boundaries between different domains and shows how they interrelate and complement one another Focuses on grand challenges and issues that matter for the future of humanity Shows different perspectives of computational thinking, understanding, and reasoning Provides a basis for scientific discoveries and enables adopting scientific theories and engineering practices from other disciplines Takes a step back to provide a human-related abstraction level that is not ultimately seen in pure technological elaborations/collections The editors provide a collection of numerous computation-related projects that form a foundation from which to cross-pollinate between different disciplines and further extensive collaboration. They present a clear and profound understanding of computing in todays world, and provide fundamental solutions to some of the most pertinent humanity-related problems.

Grand challenges for modeling and simulation

Modeling & Simulation (M&S) is making successful contributions to different areas in industry and academia. However, there are certain key issues that are preventing the field from addressing larger domains and from achieving wide-scale impact. Formulating these as grand challenges arguably focuses attention on these key issues and may bring a critical mass of effort to bear that could result in a major leap forward. This article is one of several concurrent activities aimed at reinvigorating the debate on grand challenges in M&S. These grand challenges include Big Simulation, human behavior, composability, cloud-based M&S, reproducibility in M&S research and the democratization of M&S. Two themes emerge: the need for large-scale cloud-based cyberinfrastructures for M&S and the democratized access to M&S and its outputs.

Automating humanitarian missions with a heterogeneous fleet of vehicles

Abstract The use of technology for disaster response and relief in the aftermath of natural disasters is growing. To explore the opportunity afforded by emerging technologies, this work developed an experimental automated emergency response system. Given a set of requests from the field and infrastructure information, a high-level optimization method generates a mission plan for a fleet of autonomous vehicles, including ground vehicles, fixed-wing aircraft, and delivery rotorcraft. The mission plan assigns vehicles to a list of functions and locations to be visited. Internet technology integrates the various system elements and provides a unifying environment for the physical and the modeled world in cyberspace. Guidance and control enable the vehicles to autonomously execute their plans. The movements of the fleet vehicles including their dynamic behavior are illustrated in a virtual reality interface. Preliminary experiments with a small fleet of simulated vehicles show the feasibility of such an approach.

On the Structure of Time in Computational Semantics of a Variable-Step Solver for Hybrid Behavior Analysis

Abstract Hybrid dynamic systems combine continuous and discrete behavior. Often, computational approaches approximate behavior of an analytic solution, for example, numerical integration to approximate differential equation behavior. The accuracy and computational efficiency of the integration usually depend on the complexity of the method and its implicated approximation errors, especially when repeated over iterations. This work formally defines the computational semantics of a solver in a denotational sense so as to analyze discrete- and continuous-time behavior of time-based block diagram models. A stream-based approach is used to analyze the numerical integration implemented by the solver. The resulting solver applies the principle of nonmonotonic time and so consecutive values may be computed in a temporally nonmonotonic manner. This allows shifting the evaluation points backward and forward in time. Stratification recovers a partially ordered structure in time. Solver dynamics are thus made explicit and can be studied in concert with behavior of discontinuous models parts.

A Vision on Collaborative Computation of Things for Personalized Analyses

This is a visionary introduction of a technical opportunity to engineer and maintain a more aware daily life based on continuously updated scientific results and research in such fields as Cyber Physical Systems, Internet of Things, and Modeling and Simulation for engineered systems. A conceptual framework called Computation of Things is proposed, a technical engine as an online platform is being collaboratively developed, and first results on domain convergence in both emerging technologies and applications are discussed.

Technical engine for democratization of modeling, simulations, and predictions

Computational science and engineering play a critical role in advancing both research and daily-life challenges across almost every discipline. As a society, we apply search engines, social media, and selected aspects of engineering to improve personal and professional growth. Recently, leveraging such aspects as behavioral model analysis, simulation, big data extraction, and human computation is gaining momentum. The nexus of the above facilitates mass-scale users in receiving awareness about the surrounding and themselves. In this paper, an online platform for modeling and simulation (M&S) on demand is proposed. It allows an average technologist to capitalize on any acquired information and its analysis based on scientifically-founded predictions and extrapolations. The overall objective is achieved by leveraging open innovation in the form of crowd-sourcing along with clearly defined technical methodologies and social-network-based processes. The platform aims at connecting users, developers, researchers, passionate citizens, and scientists in a professional network and opens the door to collaborative and multidisciplinary innovations. An example of a domain-specific model of a pick and place machine illustrates how to employ the platform for technical innovation and collaboration.