Capturing Assumptions while Designing a Verification Model for Embedded Systems

A formal proof of a system correctness typically holds under a number of assumptions. Leaving them implicit raises the chance of using the system in a context that violates some assumptions, which in return may invalidate the correctness proof. The goal of this paper is to show how combining informal and formal techniques in the process of modelling and formal verification helps capturing these assumptions. As we focus on embedded systems, the assumptions are about the control software, the system on which the software is running and the system’s environment. We present them as a list written in natural language that supplements the formally verified embedded system model. These two together are a better argument for system correctness than each of these given separately

Obtaining Formal Models through Non-Monotonic Refinement

When designing a model for formal verification, we want to\ud be certain that what we proved about the model also holds for the system we modelled. This raises the question of whether our model represents the system, and what makes us confident about this. By performing so called, non-monotonic refinement in the modelling process, we make the steps and decisions explicit. This helps us to (1) increase the confidence that the model represents the system, (2) structure and organize the communication with domain experts and the problem owner, and (3) identify rational steps made while modelling. We focus on embedded control systems

Escalas de la física : Una asignatura

El propósito de esta comunicación es presentar una asignatura que se ha impartido en la Universitat Politècnica de Catalunya durante los últimos cinco años. Los objetivos de la asignatura son: - Aumentar el grado de conocimientos comunes de los estudiantes de diferentes carreras técnicas. Se particularizan algunos ejercicios al campo del cuidado del ambiente que es de interés para todos ellos. - Desarrollar un método que permita reducir una situación a otra de manera inteligente y sistemática. - Mostrar las utilidades del uso de modelos a escala en la enseñanza. La técnica matemática que se utiliza es la del Análisis Dimensional, la cual requiere el conocimiento de los sistemas de ecuaciones lineales, álgebra vectorial y funciones de una o más variables. Como conclusión, creemos que la asignatura sirve para potenciar una visión unitaria de la Física y la capacidad de trabajo interdisciplinar de nuestros estudiantes. Estudiantes que deberán, con seguridad, convivir con personas de diferentes titulaciones y nacionalidades en sus lugares de trabajo real.Asociación Argentina de Energías Renovables y Medio Ambiente (ASADES

Modelling Embedded Systems by Non-Monotonic Refinement

Contains fulltext : 72720.pdf (publisher's version ) (Open Access)15 p

Deliberation and Diversity: Perceptions of Small Group Discussions by Race and Ethnicity

One of the challenges facing public deliberation scholars and practitioners is to identify deliberative processes that address inequities in interaction and foster active participation among all members of ethnically or racially diverse groups. This study draws from cocultural communication theory and uses mixed methodology to examine the experiences of citizens assigned to racially/ethnically diverse small groups who participated in “By the People: Dialogues in Democracy”—a national/local initiative and public deliberation event. One hundred participants in a local deliberation in Omaha, Nebraska, completed a postevent questionnaire, and 20 participants were subsequently interviewed. Data were analyzed to compare the perceptions of White participants and participants of color (African American, Hispanic, Native American, Asian American). Analysis of variance indicated that participants of color perceived greater communication quality and group effectiveness and experienced more satisfaction with their small groups than did Whites. Both White interviewees and interviewees of color said they valued being exposed to diverse group members and perspectives, the respectful tone of the group interaction, the facilitators’ ability to guide the interaction, and the opportunity to learn. Consistent with cocultural communication theory, participants of color specially praised the equal opportunity to speak in their groups and the experience of being heard. The results fortify the importance for public deliberation practitioners to take concerted steps to ensure racial/ethnic diversity and egalitarian interaction of members in deliberative small groups

Assessing the quality of tabular state machines through metrics.

Software metrics are widely used to measure the quality of software and to give an early indication of the efficiency of the development process in industry. There are many well-established frameworks for measuring the quality of source code through metrics, but limited attention has been paid to the quality of software models. In this article, we evaluate the quality of state machine models specified using the Analytical Software Design (ASD) tooling. We discuss how we applied a number of metrics to ASD models in an industrial setting and report about results and lessons learned while collecting these metrics. Furthermore, we recommend some quality limits for each metric and validate them on models developed in a number of industrial projects

Explaining Embedded Software Modelling Decisions

As today’s devices, gadgets and machines become more intelligent, the complexity of embedded software controlling them grows enormously. To deal with this complexity, embedded software is designed using model-based paradigms. The process of modelling is a combination of formal and creative, design steps. Because of the partially non-formal character of modelling, the relation between a model and the system cannot be expressed mathematically. Therefore, the modeller’s justification that the model represents the system adequately can only be non-formal. In this paper we discuss the nature of non-formal modelling steps and pin-point those that create a ’link’ between the model and the system. We propose steps to structure the explanation and justification of non-fomal modelling decisions. This in turn should enhance confidence that the non-formal, physical world surrounding the embedded system is adequately represented in the model

Structuring Problem Analysis for Embedded Systems Modelling

Our interest is embedded systems validation as part of the model-driven approach. To design a model, the modeller needs to obtain knowledge about the system and decide what is relevant to model and how. A part of the modelling activities is inherently informal - it cannot be formalised in such a way to constitute a basis for automated model design. This does not mean that modelling has to be chaotic. We therefore propose an informal method that structures modelling activities. In this paper we will focus on one of the method ingredients - modelling guidelines. In the industrial case study we performed, we captured modelling steps and elements in a form of a modelling handbook. The goal was to make modelling more efficient by preventing next modellers re-inventing things, but also to preserve a modelling style recognized within company's context. We show in detail what these re-usable modelling elements are, and how identifying them can be generalised for designing modelling guidelines in general. Finally, we compare our work with work of researchers that formalise problem analysis

Assessing the quality of tabular state machines through metrics.

Software metrics are widely used to measure the quality of software and to give an early indication of the efficiency of the development process in industry. There are many well-established frameworks for measuring the quality of source code through metrics, but limited attention has been paid to the quality of software models. In this article, we evaluate the quality of state machine models specified using the Analytical Software Design (ASD) tooling. We discuss how we applied a number of metrics to ASD models in an industrial setting and report about results and lessons learned while collecting these metrics. Furthermore, we recommend some quality limits for each metric and validate them on models developed in a number of industrial projects