Scenario-based verification and validation of dynamic UML specifications

The Unified Modeling Language (UML) is the result of the unification process of earlier object oriented models and notations. Verification and validation (V&V) tasks, as applied to UML specifications, enable early detection of analysis and design flaws prior to implementation. In this work, we address four V&V analysis methods for UML dynamic specifications, namely: Timing analysis and automatic V&V of timing constraints, automated Architectural-level Risk assessment, Performance Modeling and Fault Injection analysis. For each we present: approaches, methods and/or automated techniques. We use two case studies: a Cardiac Pacemaker and a simplified Automatic Teller Machine (ATM) banking subsystem, for illustrating the developed techniques

Formalisation et automatisation de la mesure des points de fonction

La méthode des points de fonction, proposée par Albrecht, permet de mesurer la taille fonctionnelle d'un logiciel durant la phase de spécification des besoins. Elle a été améliorée par l'IFPUG (International Function Points User Group). Cette méthode des points de fonction a été étendue par le groupe COSMIC (Common Software Measurement International Consortium) pour la mesure des systèmes temps réels, appelée COSMIC-FFP. Cependant, les définitions de ces deux méthodes sont ambiguës, ce qui les rend difficiles à automatiser. Dans cette thèse, nous avons formalisé la définition des points de fonction selon la méthode d'IFPUG pour mesurer des spécifications écrites en langage B. Nous avons également formalisé la définition de COSMIC-FFP pour des spécifications écrites avec la notation de Rational Rose RealTime (RRRT). De plus, nous avons développé un outil, [Special characters omitted.], qui permet de mesurer automatiquement COSMIC-FFP pour des spécifications RRRT. Nos définitions formelles permettent de lever plusieurs ambiguïtés et de rendre ces mesures objectives, ce qui permettra d'éliminer la variance dans le processus de mesure.La formalisation permet également l'automatisation de la mesure

CHANGE-READY MPC SYSTEMS AND PROGRESSIVE MODELING: VISION, PRINCIPLES, AND APPLICATIONS

The last couple of decades have witnessed a level of fast-paced development of new ideas, products, manufacturing technologies, manufacturing practices, customer expectations, knowledge transition, and civilization movements, as it has never before. In today\u27s manufacturing world, change became an intrinsic characteristic that is addressed everywhere. How to deal with change, how to manage it, how to bind to it, how to steer it, and how to create a value out of it, were the key drivers that brought this research to existence. Change-Ready Manufacturing Planning and Control (CMPC) systems are presented as the first answer. CMPC characteristics, change drivers, and some principles of Component-Based Software Engineering (CBSE) are interwoven to present a blueprint of a new framework and mind-set in the manufacturing planning and control field, CMPC systems. In order to step further and make the internals of CMPC systems/components change-ready, an enabling modeling approach was needed. Progressive Modeling (PM), a forward-looking multi-disciplinary modeling approach, is developed in order to modernize the modeling process of today\u27s complex industrial problems and create pragmatic solutions for them. It is designed to be pragmatic, highly sophisticated, and revolves around many seminal principles that either innovated or imported from many disciplines: Systems Analysis and Design, Software Engineering, Advanced Optimization Algorisms, Business Concepts, Manufacturing Strategies, Operations Management, and others. Problems are systemized, analyzed, componentized; their logic and their solution approaches are redefined to make them progressive (ready to change, adapt, and develop further). Many innovations have been developed in order to enrich the modeling process and make it a well-assorted toolkit able to address today\u27s tougher, larger, and more complex industrial problems. PM brings so many novel gadgets in its toolbox: function templates, advanced notation, cascaded mathematical models, mathematical statements, society of decision structures, couplers--just to name a few. In this research, PM has been applied to three different applications: a couple of variants of Aggregate Production Planning (APP) Problem and the novel Reconfiguration and Operations Planning (ROP) problem. The latest is pioneering in both the Reconfigurable Manufacturing and the Operations Management fields. All the developed models, algorithms, and results reveal that the new analytical and computational power gained by PM development and demonstrate its ability to create a new generation of unmatched large scale and scope system problems and their integrated solutions. PM has the potential to be instrumental toolkit in the development of Reconfigurable Manufacturing Systems. In terms of other potential applications domain, PM is about to spark a new paradigm in addressing large-scale system problems of many engineering and scientific fields in a highly pragmatic way without losing the scientific rigor

Proceedings of the Doctoral Consortium in Computer Science (JIPII 2021)

Actas de las Jornadas de Investigación Predoctoral en Ingeniería InformáticaThis volume contains the proceedings of the Primeras Jornadas de Investigación Predoctoral en Ingeniería Informática - First Doctoral Consortium in Computer Science, JIPII 2021, which was held online on June 15th, 2021. The aim of JIPII 2021 was to provide a forum for PhD students to present and discuss their research under the guidance of a panel of senior researchers. The advances in their PhD theses under development in the Doctoral Program in Computer Science were presented in the Consortium. This Doctoral Program belongs to the Doctoral School of the University of Cadiz (EDUCA). Different stages of research were covered, from the most incipient phase, such as the PhD Thesis plans (or even a Master’s Thesis), to the most advanced phases in which the defence of the PhD Thesis is imminent. We enjoyed twenty very nice and interesting talks, organized in four sessions. We had a total of fifty participants, including speakers and attendees, with an average of thirty-two people in the morning sessions and an average of twenty people in the afternoon sessions. Several people contributed to the success of JIPII 2021. We are grateful to the Academic Committee of the Doctoral Program in Computer Science and the School of Engineering for their support. We would like also to thank the Program Committee for their work in reviewing the papers, as well as all the students and supervisors for their interest and participation. Finally, the proceedings have been published by the Department of Computer Science and Engineering. We hope that you find the proceedings useful, interesting, and challenging

Multi-Agent Systems

A multi-agent system (MAS) is a system composed of multiple interacting intelligent agents. Multi-agent systems can be used to solve problems which are difficult or impossible for an individual agent or monolithic system to solve. Agent systems are open and extensible systems that allow for the deployment of autonomous and proactive software components. Multi-agent systems have been brought up and used in several application domains

Reconfigurable middleware architectures for large scale sensor networks

Wireless sensor networks, in an effort to be energy efficient, typically lack the high-level abstractions of advanced programming languages. Though strong, the dichotomy between these two paradigms can be overcome. The SENSIX software framework, described in this dissertation, uniquely integrates constraint-dominated wireless sensor networks with the flexibility of object-oriented programming models, without violating the principles of either. Though these two computing paradigms are contradictory in many ways, SENSIX bridges them to yield a dynamic middleware abstraction unifying low-level resource-aware task reconfiguration and high-level object recomposition. Through the layered approach of SENSIX, the software developer creates a domain-specific sensing architecture by defining a customized task specification and utilizing object inheritance. In addition, SENSIX performs better at large scales (on the order of 1000 nodes or more) than other sensor network middleware which do not include such unified facilities for vertical integration