10 resultados para Constraint programming (Computer science)

em Aston University Research Archive


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In the computer science community, there is considerable debate about the appropriate sequence for introducing object-oriented concepts to novice programmers. Research into novice programming has struggled to identify the critical aspects that would provide a consistently successful approach to teaching introductory object-oriented programming. Starting from the premise that the conceptions of a task determine the type of output from the task, assisting novice programmers to become aware of what the required output should be, may lay a foundation for improving learning. This study adopted a phenomenographic approach. Thirty one practitioners were interviewed about the ways in which they experience object-oriented programming and categories of description and critical aspects were identified. These critical aspects were then used to examine the spaces of learning provided in twenty introductory textbooks. The study uncovered critical aspects that related to the way that practitioners expressed their understanding of an object-oriented program and the influences on their approach to designing programs. The study of the textbooks revealed a large variability in the cover of these critical aspects.

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We present the prototype tool CADS* for the computer-aided development of an important class of self-* systems, namely systems whose components can be modelled as Markov chains. Given a Markov chain representation of the IT components to be included into a self-* system, CADS* automates or aids (a) the development of the artifacts necessary to build the self-* system; and (b) their integration into a fully-operational self-* solution. This is achieved through a combination of formal software development techniques including model transformation, model-driven code generation and dynamic software reconfiguration.

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Object-oriented programming is seen as a difficult skill to master. There is considerable debate about the most appropriate way to introduce novice programmers to object-oriented concepts. Is it possible to uncover what the critical aspects or features are that enhance the learning of object-oriented programming? Practitioners have differing understandings of the nature of an object-oriented program. Uncovering these different ways of understanding leads to agreater understanding of the critical aspects and their relationship tothe structure of the program produced. A phenomenographic studywas conducted to uncover practitioner understandings of the nature of an object-oriented program. The study identified five levels of understanding and three dimensions of variation within these levels. These levels and dimensions of variation provide a framework for fostering conceptual change with respect to the nature of an object-oriented program.

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Collaborative working with the aid of computers is increasing rapidly due to the widespread use of computer networks, geographic mobility of people, and small powerful personal computers. For the past ten years research has been conducted into this use of computing technology from a wide variety of perspectives and for a wide range of uses. This thesis adds to that previous work by examining the area of collaborative writing amongst groups of people. The research brings together a number of disciplines, namely sociology for examining group dynamics, psychology for understanding individual writing and learning processes, and computer science for database, networking, and programming theory. The project initially looks at groups and how they form, communicate, and work together, progressing on to look at writing and the cognitive processes it entails for both composition and retrieval. The thesis then details a set of issues which need to be addressed in a collaborative writing system. These issues are then followed by developing a model for collaborative writing, detailing an iterative process of co-ordination, writing and annotation, consolidation, and negotiation, based on a structured but extensible document model. Implementation issues for a collaborative application are then described, along with various methods of overcoming them. Finally the design and implementation of a collaborative writing system, named Collaborwriter, is described in detail, which concludes with some preliminary results from initial user trials and testing.

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We argue that, for certain constrained domains, elaborate model transformation technologies-implemented from scratch in general-purpose programming languages-are unnecessary for model-driven engineering; instead, lightweight configuration of commercial off-the-shelf productivity tools suffices. In particular, in the CancerGrid project, we have been developing model-driven techniques for the generation of software tools to support clinical trials. A domain metamodel captures the community's best practice in trial design. A scientist authors a trial protocol, modelling their trial by instantiating the metamodel; customized software artifacts to support trial execution are generated automatically from the scientist's model. The metamodel is expressed as an XML Schema, in such a way that it can be instantiated by completing a form to generate a conformant XML document. The same process works at a second level for trial execution: among the artifacts generated from the protocol are models of the data to be collected, and the clinician conducting the trial instantiates such models in reporting observations-again by completing a form to create a conformant XML document, representing the data gathered during that observation. Simple standard form management tools are all that is needed. Our approach is applicable to a wide variety of information-modelling domains: not just clinical trials, but also electronic public sector computing, customer relationship management, document workflow, and so on. © 2012 Springer-Verlag.

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Population measures for genetic programs are defined and analysed in an attempt to better understand the behaviour of genetic programming. Some measures are simple, but do not provide sufficient insight. The more meaningful ones are complex and take extra computation time. Here we present a unified view on the computation of population measures through an information hypertree (iTree). The iTree allows for a unified and efficient calculation of population measures via a basic tree traversal. © Springer-Verlag 2004.

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A phenomenographic study uncovers variations in the way that the subjects are aware of a phenomenon. In the categories of description that represent the variations in awareness there are features that, through their variation, define the characteristics of the categories. Teaching seeks to foster a change in the way that the learner is aware of a phenomenon through opening up a space of learning. This paper outlines the way that the outcome spaces from a phenomenographic study can be used to plan a teaching programme that utilises variations in the features. It discusses a strategy for teaching programming based on a phenomenographic study of practitioner conceptions of an object-oriented program. The strategy covers features related to the nature of an object-oriented program. Copyright 2010 ACM.

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This book constitutes the refereed proceedings of the 14th International Conference on Parallel Problem Solving from Nature, PPSN 2016, held in Edinburgh, UK, in September 2016. The total of 93 revised full papers were carefully reviewed and selected from 224 submissions. The meeting began with four workshops which offered an ideal opportunity to explore specific topics in intelligent transportation Workshop, landscape-aware heuristic search, natural computing in scheduling and timetabling, and advances in multi-modal optimization. PPSN XIV also included sixteen free tutorials to give us all the opportunity to learn about new aspects: gray box optimization in theory; theory of evolutionary computation; graph-based and cartesian genetic programming; theory of parallel evolutionary algorithms; promoting diversity in evolutionary optimization: why and how; evolutionary multi-objective optimization; intelligent systems for smart cities; advances on multi-modal optimization; evolutionary computation in cryptography; evolutionary robotics - a practical guide to experiment with real hardware; evolutionary algorithms and hyper-heuristics; a bridge between optimization over manifolds and evolutionary computation; implementing evolutionary algorithms in the cloud; the attainment function approach to performance evaluation in EMO; runtime analysis of evolutionary algorithms: basic introduction; meta-model assisted (evolutionary) optimization. The papers are organized in topical sections on adaption, self-adaption and parameter tuning; differential evolution and swarm intelligence; dynamic, uncertain and constrained environments; genetic programming; multi-objective, many-objective and multi-level optimization; parallel algorithms and hardware issues; real-word applications and modeling; theory; diversity and landscape analysis.