147 research outputs found

    Vérification interactive de propriétés à l'exécution d'un programme avec un débogueur

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    National audienceLe monitoring est l'étude d'un système pendant son exécution, en surveillant les évènements qui y entrent et qui en sortent, afin de découvrir, vérifier ou pour faire respecter des propriétés à l'exécution. Le débogage est l'étude d'un système pendant son exécution afin de trouver et comprendre ses dysfonctionnements dans le but de les corriger, en inspectant son état interne, de manière interactive. Dans ce papier, nous combinons le monitoring et le débogage en définissant un moyen efficace et pratique de vérifier automatiquement des propriétés à l'exécution d'un programme à l'aide d'un débogueur afin d'aider à détecter des anomalies dans son code, en conservant le caractère interactif du débogage classique

    Farmers Awareness and Response to Climate Change: A Case Study of the North Bank Region, The Gambia

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    Rain-fed agriculture, which is the backbone of most sub-Saharan economies is seriously under threat due to climate change. Consequently, for farmers to sustain their livelihoods and increase productivity, there is the need for them to be aware of climate change and how they can sustainably respond to it. This study focused on farmers’ awareness of climate change and their response to its effect in the North Bank Region of The Gambia. Data for the study was collected from 258 farmer household heads selected through a multi-stage sampling technique and 9 focus group discussions. Descriptive statistics and climate change awareness index (CCAI) were used to analyze the data obtained from the households. The findings revealed that majority (80.6%) of the farmers were aware of climate change with an average awareness index of 0.586 (58.6%). Also, an overwhelming majority of 93.41% of the farmers used crop diversifications, drought resistant cultivars, early maturing varieties among others as response strategy to climate change. The study concludes that farmers in the study area are fairly aware of climate change. Farmers are recommended to form farmer associations to enable easy access to more climate change education/ training from Donor and Government agencies to improve their climate change knowledge and enhance their adaptive capacity. Keywords: Climate change, Response, Climate change Awareness Index, The Gambi

    Educational Technology and Related Education Conferences for January to June 2011 - November 11, 2010

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    If you attend the same conferences each year, you don’t need to scan this list. This list is your opportunity to “push the envelope” by trying something new. There are hundreds of professional development events that may give you a different perspective or help you learn a new skill. Rather than attend the same event you always do, scan this list and investigate conferences, symposiums, or workshops you have never attended. The list below covers selected events focused primarily on the use of technology in educational settings and on teaching, learning, and educational administration. Only listings until June 2011 are complete as dates, locations, or URLs are not available for a number of events held after June 2011. A Word 2003 format is used to enable people who do not have access to Word 2007 or higher version and those with limited or high-cost Internet access to find a conference that is congruent with their interests or obtain conference proceedings. (If you are seeking a more interactive listing, refer to online conference sites.) Consider using the “Find” tool under Microsoft Word’s “Edit” tab or similar tab in OpenOffice to locate the name of a particular conference, association, city, or country. If you enter the country “United Kingdom” in the “Find” tool, all conferences that occur in the United Kingdom will be highlighted. Then, “cut and paste” a list of suitable events for yourself and your colleagues. Please note that events, dates, titles, and locations may change; thus, CHECK the specific conference website. Note also that some events will be cancelled at a later date. All Internet addresses were verified at the time of publication. No liability is assumed for any errors that may have been introduced inadvertently during the assembly of this conference list. If possible, please do not remove the contact information when you re-distribute the list as that is how I receive updates and corrections. If you publish the list on the web, please note its source

    DREQUS: an approach for the Discovery of REQuirements Using Scenarios

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    ABSTRACT: Requirements engineering is recognized as a complex cognitive problem-solving process that takes place in an unstructured and poorly-understood problem context. Requirements elicitation is the activity generally regarded as the most crucial step in the requirements engineering process. The term “elicitation” is preferred to “capture”, to avoid the suggestion that requirements are out there to be collected. Information gathered during requirements elicitation often has to be interpreted, analyzed, modeled, and validated before the requirements engineer can feel confident that a complete set of requirements of a system have been obtained. Requirements elicitation comprises the set of activities that enable discovering, understanding, and documenting the goals and motives for building a proposed software system. It also involves identifying the requirements that the resulting system must satisfy in to achieve these goals. The requirements to be elicited may range from modifications to well-understood problems and systems (i.e. software upgrades), to hazy understandings of new problems being automated, to relatively unconstrained requirements that are open to innovation (e.g. mass-market software). Requirements elicitation remains problematic; missing or mistaken requirements still delay projects and cause cost overruns. No firm definition has matured for requirements elicitation in comparison to other areas of requirements engineering. This research is aimed to improve the results of the requirements elicitation process directly impacting the quality of the software products derived from them

    Apport du Web sémantique au travail collaboratif : Application à l'édition d'un document d'information sur les risques majeurs

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    http://www.irit.fr/~Guillaume.Cabanac/docs/fjc2014/fjc2014actes.pdf" Collaborer " , " travailler ensemble " , ce sont des réalités familières à chacun d'entre nous. Or les techniques ont progressé et ont pris un nouveau tournant avec l'arrivée du numérique dans l'entreprise. Bien que l'introduction du numérique ne se fasse pas sans difficultés, de nouveaux outils continuent d'apparaître : le travail collaboratif assisté par ordinateur est progressivement devenu un domaine d'étude à part entière. Notre recherche s'inscrit dans ce courant et étudie les apports possibles des technologies du Web sémantique au travail collaboratif. Ces technologies, en apportant les concepts d'ontologie, de métadonnées, d'inférence, participent au passage d'un système d'information à un système plus orienté connaissance. Devant ce vaste champ d'étude, nous avons pour nous guider un cas d'application qui est d'ailleurs à l'origine de ces travaux. Il s'agit du DDRM " Dossier Départemental sur les Risques Majeurs " un document administratif réalisé sous la supervision du préfet et qui compile les informations essentielles concernant les risques naturels et technologiques majeurs connus sur le territoire d'un département. Ce document d'information et de prévention destiné aux citoyens, doit être actualisé tous les cinq ans, étape nécessitant le concours de plusieurs acteurs issus d'horizons et de métiers différents. C'est ici qu'intervient la possibilité d'améliorer ce travail, qui est par essence collaboratif, à l'aide des nouvelles technologies et en particulier celles issues du Web sémantique. Nous imaginons que le système, plongé dans le Web 2.0 et les Linked Open Data , favorisera les échanges entre départements

    The relationship between search based software engineering and predictive modeling

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    Search Based Software Engineering (SBSE) is an approach to software engineering in which search based optimization algorithms are used to identify optimal or near optimal solutions and to yield insight. SBSE techniques can cater for multiple, possibly competing objectives and/or constraints and applications where the potential solution space is large and complex. This paper will provide a brief overview of SBSE, explaining some of the ways in which it has already been applied to construction of predictive models. There is a mutually beneficial relationship between predictive models and SBSE. The paper sets out eleven open problem areas for Search Based Predictive Modeling and describes how predictive models also have role to play in improving SBSE

    Engineering security into distributed systems: a survey of methodologies

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    Rapid technological advances in recent years have precipitated a general shift towards software distribution as a central computing paradigm. This has been accompanied by a corresponding increase in the dangers of security breaches, often causing security attributes to become an inhibiting factor for use and adoption. Despite the acknowledged importance of security, especially in the context of open and collaborative environments, there is a growing gap in the survey literature relating to systematic approaches (methodologies) for engineering secure distributed systems. In this paper, we attempt to fill the aforementioned gap by surveying and critically analyzing the state-of-the-art in security methodologies based on some form of abstract modeling (i.e. model-based methodologies) for, or applicable to, distributed systems. Our detailed reviews can be seen as a step towards increasing awareness and appreciation of a range of methodologies, allowing researchers and industry stakeholders to gain a comprehensive view of the field and make informed decisions. Following the comprehensive survey we propose a number of criteria reflecting the characteristics security methodologies should possess to be adopted in real-life industry scenarios, and evaluate each methodology accordingly. Our results highlight a number of areas for improvement, help to qualify adoption risks, and indicate future research directions.Anton V. Uzunov, Eduardo B. Fernandez, Katrina Falkne
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