989 resultados para PROGRAMMING-PROBLEMS
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Several standards appeared in recent years to formalize the metadata of learning objects, but they are still insufficient to fully describe a specialized domain. In particular, the programming exercise domain requires interdependent resources (e.g. test cases, solution programs, exercise description) usually processed by different services in the programming exercise life-cycle. Moreover, the manual creation of these resources is time-consuming and error-prone leading to what is an obstacle to the fast development of programming exercises of good quality. This paper focuses on the definition of an XML dialect called PExIL (Programming Exercises Interoperability Language). The aim of PExIL is to consolidate all the data required in the programming exercise life-cycle, from when it is created to when it is graded, covering also the resolution, the evaluation and the feedback. We introduce the XML Schema used to formalize the relevant data of the programming exercise life-cycle. The validation of this approach is made through the evaluation of the usefulness and expressiveness of the PExIL definition. In the former we present the tools that consume the PExIL definition to automatically generate the specialized resources. In the latter we use the PExIL definition to capture all the constraints of a set of programming exercises stored in a learning objects repository.
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Learning computer programming requires solving programming exercises. In computer programming courses teachers need to assess and give feedback to a large number of exercises. These tasks are time consuming and error-prone since there are many aspects relating to good programming that should be considered. In this context automatic assessment tools can play an important role helping teachers in grading tasks as well to assist students with automatic feedback. In spite of its usefulness, these tools lack integration mechanisms with other eLearning systems such as Learning Management Systems, Learning Objects Repositories or Integrated Development Environments. In this paper we provide a survey on programming evaluation systems. The survey gathers information on interoperability features of these systems, categorizing and comparing them regarding content and communication standardization. This work may prove useful to instructors and computer science educators when they have to choose an assessment system to be integrated in their e-Learning environment.
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This paper presents a tool called Petcha that acts as an automated Teaching Assistant in computer programming courses. The ultimate objective of Petcha is to increase the number of programming exercises effectively solved by students. Petcha meets this objective by helping both teachers to author programming exercises and students to solve them. It also coordinates a network of heterogeneous systems, integrating automatic program evaluators, learning management systems, learning object repositories and integrated programming environments. This paper presents the concept and the design of Petcha and sets this tool in a service oriented architecture for managing learning processes based on the automatic evaluation of programming exercises. The paper presents also a case study that validates the use of Petcha and of the proposed architecture.
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Assessment plays a vital role in learning. This is certainly the case with assessment of computer programs, both in curricular and competitive learning. The lack of a standard – or at least a widely used format – creates a modern Ba- bel tower made of Learning Objects, of assessment items that cannot be shared among automatic assessment systems. These systems whose interoperability is hindered by the lack of a common format include contest management systems, evaluation engines, repositories of learning objects and authoring tools. A prag- matical approach to remedy this problem is to create a service to convert among existing formats. A kind of translation service specialized in programming prob- lems formats. To convert programming exercises on-the-fly among the most used formats is the purpose of the BabeLO – a service to cope with the existing Babel of Learning Object formats for programming exercises. BabeLO was designed as a service to act as a middleware in a network of systems typically used in auto- matic assessment of programs. It provides support for multiple exercise formats and can be used by: evaluation engines to assess exercises regardless of its format; repositories to import exercises from various sources; authoring systems to create exercises in multiple formats or based on exercises from other sources. This paper analyses several of existing formats to highlight both their differ- ences and their similar features. Based on this analysis it presents an approach to extensible format conversion. It presents also the features of PExIL, the pivotal format in which the conversion is based; and the function definitions of the proposed service – BabeLO. Details on the design and implementation of BabeLO, including the service API and the interfaces required to extend the conversion to a new format, are also provided. To evaluate the effectiveness and efficiency of this approach this paper reports on two actual uses of BabeLO: to relocate exercises to a different repository; and to use an evaluation engine in a network of heterogeneous systems.
Resumo:
Several standards have appeared in recent years to formalize the metadata of learning objects, but they are still insufficient to fully describe a specialized domain. In particular, the programming exercise domain requires interdependent resources (e.g. test cases, solution programs, exercise description) usually processed by different services in the programming exercise lifecycle. Moreover, the manual creation of these resources is time-consuming and error-prone, leading to an obstacle to the fast development of programming exercises of good quality. This chapter focuses on the definition of an XML dialect called PExIL (Programming Exercises Interoperability Language). The aim of PExIL is to consolidate all the data required in the programming exercise lifecycle from when it is created to when it is graded, covering also the resolution, the evaluation, and the feedback. The authors introduce the XML Schema used to formalize the relevant data of the programming exercise lifecycle. The validation of this approach is made through the evaluation of the usefulness and expressiveness of the PExIL definition. In the former, the authors present the tools that consume the PExIL definition to automatically generate the specialized resources. In the latter, they use the PExIL definition to capture all the constraints of a set of programming exercises stored in a learning objects repository.
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Existent computer programming training environments help users to learn programming by solving problems from scratch. Nevertheless, initiating the resolution of a program can be frustrating and demotivating if the student does not know where and how to start. Skeleton programming facilitates a top-down design approach, where a partially functional system with complete high level structures is available, so the student needs only to progressively complete or update the code to meet the requirements of the problem. This paper presents CodeSkelGen - a program skeleton generator. CodeSkelGen generates skeleton or buggy Java programs from a complete annotated program solution provided by the teacher. The annotations are formally described within an annotation type and processed by an annotation processor. This processor is responsible for a set of actions ranging from the creation of dummy methods to the exchange of operator types included in the source code. The generator tool will be included in a learning environment that aims to assist teachers in the creation of programming exercises and to help students in their resolution.
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A indústria automóvel no que respeita à gestão oficinal de qualidade é uma referência de dimensão e nível mundial. O constante avanço da indústria automóvel, o ciclo de vida dos produtos (automóveis) cada vez mais curtos e a competitividade entre empresas, requer uma procura constante de novas ferramentas de melhoria na gestão oficinal. Neste trabalho, centrado na gestão oficinal no setor automóvel, procuram-se introduzir novas abordagens que visem combater o decréscimo da rentabilidade neste setor. Como se depreende do exposto anteriormente, o objetivo principal desta dissertação é propor e avaliar (validar) propostas de melhoria que visem o aumento da rentabilidade financeira da empresa AMC – Auto Mecânica de Cambra, Lda. Com vista à prossecução deste objetivo foram definidos os seguintes objetivos intercalares na AMC: - Análise e levantamento dos problemas; - Identificação de potenciais causas; - Formulação de ações de propostas de melhoria na gestão da empresa; - Programação das ações e avaliação de resultados alcançados; A estrutura definida nesta dissertação após a sua introdução no capítulo 1 centra-se no capítulo 2 na apresentação da empresa AMC, com a descrição dos problemas levantados atendendo às vertentes mais críticas. Seguidamente, no capítulo 3, com ferramentas de análise de problemas, serão encontradas as causas raiz destes problemas. Posteriormente no capítulo seguinte serão criados planos de ações para a resolução das causas. No capítulo 4 as ações serão implementadas e avaliadas para garantir a sua eficácia e eficiência. Por fim, no capítulo 5 são descritas as conclusões e os desenvolvimentos futuros enquadráveis com a melhoria contínua da AMC. Como conclusão, este trabalho, mostra que várias propostas de melhoria implementadas trouxeram ganhos efetivos para a empresa e que futuras propostas são potencialmente válidas num futuro próximo. Esta dissertação com ligação direta à AMC tem igualmente dados que podem ser extrapolados e adaptados a outras empresas do mesmo setor. O objetivo principal deste estudo é a análise e o levantamento dos problemas com a utilização de ferramentas tais como: Benchmarking, Diagrama causa-efeito, ciclo PDCA, análise de SWOT e indicadores operativos da oficina.
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Within a large set of renewable energies being explored to tackle energy sourcing problems, bioenergy can represent an attractive solution if effectively managed. The supply chain design supported by mathematical programming can be used as a decision support tool to the successful bioenergy production systems establishment. This strategic decision problem is addressed in this paper where we intent to study the design of the residual forestry biomass to bioelectricity production in the Portuguese context. In order to contribute to attain better solutions a mixed integer linear programming (MILP) model is developed and applied in order to optimize the design and planning of the bioenergy supply chain. While minimizing the total supply chain cost the production energy facilities capacity and location are defined. The model also includes the optimal selection of biomass amounts and sources, the transportation modes selection, and links that must be established for biomass transportation and products delivers to markets. Results illustrate the positive contribution of the mathematical programming approach to achieve viable economic solutions. Sensitivity analysis on the most uncertain parameters was performed: biomass availability, transportation costs, fixed operating costs and investment costs. (C) 2015 Elsevier Ltd. All rights reserved.
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Dissertação para a obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia
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Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Informática, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia
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The minimum interval graph completion problem consists of, given a graph G = ( V, E ), finding a supergraph H = ( V, E ∪ F ) that is an interval graph, while adding the least number of edges |F| . We present an integer programming formulation for solving the minimum interval graph completion problem recurring to a characteri- zation of interval graphs that produces a linear ordering of the maximal cliques of the solution graph.
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A methodology to increase the probability of delivering power to any load point through the identification of new investments in distribution network components is proposed in this paper. The method minimizes the investment cost as well as the cost of energy not supplied in the network. A DC optimization model based on mixed integer non-linear programming is developed considering the Pareto front technique in order to identify the adequate investments in distribution networks components which allow increasing the probability of delivering power for any customer in the distribution system at the minimum possible cost for the system operator, while minimizing the energy not supplied cost. Thus, a multi-objective problem is formulated. To illustrate the application of the proposed methodology, the paper includes a case study which considers a 180 bus distribution network
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This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding the management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.