Abstraction and Assume-Guarantee Reasoning for Automated Software Verification

Compositional verification and abstraction are the key techniques to address the state explosion problem associated with model checking of concurrent software. A promising compositional approach is to prove properties of a system by checking properties of its components in an assume-guarantee style. This article proposes a framework for performing abstraction and assume-guarantee reasoning of concurrent C code in an incremental and fully automated fashion. The framework uses predicate abstraction to extract and refine finite state models of software and it uses an automata learning algorithm to incrementally construct assumptions for the compositional verification of the abstract models. The framework can be instantiated with different assume-guarantee rules. We have implemented our approach in the COMFORT reasoning framework and we show how COMFORT out-performs several previous software model checking approaches when checking safety properties of non-trivial concurrent programs

Evaluation of Clinical Reasoning of Nursing Students in the Clinical Setting

The primary focus of nursing education in the 21st century is to graduate students with well-developed critical thinking and clinical reasoning skills. This descriptive case study explored the perceptions of 6 faculty and 6 unit staff nurses concerning the assessment of critical thinking and clinical reasoning skills of nursing students in the clinical setting. Benner\u27s novice to expert theory served as the conceptual framework for the research. The guiding research questions focused on faculty and staff perceptions concerning unit staff nurses\u27 level of preparedness to assess the critical thinking and clinical reasoning ability of nursing students, and explored how faculty and unit staff nurses perceived the process of evaluating nursing students\u27 clinical reasoning and critical thinking skills in the clinical setting. Data were collected using semi structured interview questions, then coded and analyzed following Creswell\u27s approach. This analysis identified six themes: (a) lack of consistency, (b) faculty and staff clinical expectations of students, (c) barriers to clinical education, (d) faculty and staff differences in educational definitions, (e) faculty and staff comfort level with students, and (f) resources needed for clinical education. Learning how faculty and staff nurses assess student nurses\u27 ability to demonstrate effective clinical reasoning and critical thinking skills can positively impact social change in nursing education on the local and state level by informing best practice in how critical thinking and clinical reasoning are taught and assessed in nursing education. This facilitates graduating nurses who are prepared to deliver patient care that affect positive outcomes

Security enhancement with foreground trust, comfort, and ten commandments for real people

Security as an enabling paradigm has not succeeded half as well as we might have hoped. Systems are broken or breakable, and users (people) have something of a lack of faith, understanding, or patience with security measures that exist. Whilst secure systems and solutions are the backbone of a working interconnected system of systems, they are not people-oriented, and they are oftentimes arcane enough to have an air of ‘security theatre’ about them. We can also assume that they will continue to grow in both complexity and application if we continue as we are in our arms race. To answer what we perceive to be a problem here, we are working on the integration of socio-psychological notions of trust into computational systems where it makes sense (both human- and system-facing). This work includes the development of our Device Comfort paradigm and architecture, wherein mobile devices and nodes in infrastructures have a embedded notion of comfort that they can use to reason about their use, behaviour, and users. This notion, contextually integrated with the environment the device is in, aids in decision making with regard to, for instance, information flow, security posture, and user-oriented advice. Most importantly, the notion embeds trust reasoning and communication into the device, with which the user can be aided to un- derstand situation, risk, and actions by device, infrastructure, and themselves - which we call Foreground Trust, after Dwyer. We conjecture that comfort and foreground trust both enhance security for devices and increase the under- standing of security for the user, through use of human-comprehensible and anthropomorphic concepts. In this paper, we discuss some security problems, address the misnomer of trusted computing, and present an overview of com- fort and foreground trust. Finally, we briely present our ten commandments for trust-reasoning models such as those contained within Device Comfort, in the hope that they are of some use in security also

Microservices and Machine Learning Algorithms for Adaptive Green Buildings

In recent years, the use of services for Open Systems development has consolidated and strengthened. Advances in the Service Science and Engineering (SSE) community, promoted by the reinforcement of Web Services and Semantic Web technologies and the presence of new Cloud computing techniques, such as the proliferation of microservices solutions, have allowed software architects to experiment and develop new ways of building open and adaptable computer systems at runtime. Home automation, intelligent buildings, robotics, graphical user interfaces are some of the social atmosphere environments suitable in which to apply certain innovative trends. This paper presents a schema for the adaptation of Dynamic Computer Systems (DCS) using interdisciplinary techniques on model-driven engineering, service engineering and soft computing. The proposal manages an orchestrated microservices schema for adapting component-based software architectural systems at runtime. This schema has been developed as a three-layer adaptive transformation process that is supported on a rule-based decision-making service implemented by means of Machine Learning (ML) algorithms. The experimental development was implemented in the Solar Energy Research Center (CIESOL) applying the proposed microservices schema for adapting home architectural atmosphere systems on Green Buildings

Modeling and analyzing variability for mobile information systems

Abstract. Advances in size, power, and ubiquity of computing, sensors, and communication technology made possible the development of mobile or nomadic information systems. Variability of location and system behavior is a central issue in mobile information systems, where behavior of software has to change and re-adapt to the different location settings. This paper concerns modeling and analysis of the complementary relation between software and location variability. We use graphical and formal location modeling techniques, show how to elicit and use location model in conjunction with Tropos goal-oriented framework, and introduce automated analysis on the location-based models.

Update of time-invalid information in Knowledge Bases through Mobile Agents

In this paper, we investigate the use of a mobile, autonomous agent to update knowledge bases containing statements that lose validity with time. This constitutes a key issue in terms of knowledge acquisition and representation, because dynamic data need to be constantly re-evaluated to allow reasoning. We focus on the way to represent the time- validity of statements in a knowledge base, and on the use of a mobile agent to update time-invalid statements while planning for “information freshness” as the main objective. We propose to use Semantic Web standards, namely the RDF model and the SPARQL query language, to represent time-validity of information and decide how long this will be considered valid. Using such a representation, a plan is created for the agent to update the knowledge, focusing mostly on guaranteeing the time-validity of the information collected. To show the feasibility of our approach and discuss its limitations, we test its implementation on scenarios in the working environment of our research lab, where an autonomous robot is used to sense temperature, humidity, wifi signal and number of people on demand, updating the knowledge base with time- valid information

A fuzzy approach to building thermal systems optimization.

Optimization of building thermal systems is treated in the paper in the framework of fuzzy mathematical programming. This new approach allows to formulate more precisely the problem which compromises energy saving and thermal comfort satisfaction under given constraints. Fuzzy optimization problem is solved analytically under some assumptions. An example illustrates the viability of the approach proposed. A solution which significantly (with 38%) improves comfort is found which is more energetically expensive with only 0.6%. (c) IFS

Improving argumentation-based recommender systems through context-adaptable selection criteria

Recommender Systems based on argumentation represent an important proposal where the recommendation is supported by qualitative information. In these systems, the role of the comparison criterion used to decide between competing arguments is paramount and the possibility of using the most appropriate for a given domain becomes a central issue; therefore, an argumentative recommender system that offers an interchangeable argument comparison criterion provides a significant ability that can be exploited by the user. However, in most of current recommender systems, the argument comparison criterion is either fixed, or codified within the arguments. In this work we propose a formalization of context-adaptable selection criteria that enhances the argumentative reasoning mechanism. Thus, we do not propose of a new type of recommender system; instead we present a mechanism that expand the capabilities of existing argumentation-based recommender systems. More precisely, our proposal is to provide a way of specifying how to select and use the most appropriate argument comparison criterion effecting the selection on the user´s preferences, giving the possibility of programming, by the use of conditional expressions, which argument preference criterion has to be used in each particular situation.Fil: Teze, Juan Carlos Lionel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación; Argentina. Universidad Nacional de Entre Ríos; ArgentinaFil: Gottifredi, Sebastián. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación; ArgentinaFil: García, Alejandro Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación; ArgentinaFil: Simari, Guillermo Ricardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación; Argentin