17 resultados para Program Analysis
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Concurrent programming is a difficult and error-prone task because the programmer must reason about multiple threads of execution and their possible interleavings. A concurrent program must synchronize the concurrent accesses to shared memory regions, but this is not enough to prevent all anomalies that can arise in a concurrent setting. The programmer can misidentify the scope of the regions of code that need to be atomic, resulting in atomicity violations and failing to ensure the correct behavior of the program. Executing a sequence of atomic operations may lead to incorrect results when these operations are co-related. In this case, the programmer may be required to enforce the sequential execution of those operations as a whole to avoid atomicity violations. This situation is specially common when the developer makes use of services from third-party packages or modules. This thesis proposes a methodology, based on the design by contract methodology, to specify which sequences of operations must be executed atomically. We developed an analysis that statically verifies that a client of a module is respecting its contract, allowing the programmer to identify the source of possible atomicity violations.
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Tese de doutoramento em Ciências da Educação
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Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação Geográfica
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Dissertation to obtain the degree of Doctor in Electrical and Computer Engineering, specialization of Collaborative Networks
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Dissertação para obtenção do Grau de Mestre em Lógica Computacional
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Relatório de Estágio de Mestrado em Ciência Política e Relações Internacionais Globalização e Ambiente
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Dissertação para obtenção do Grau de Doutor em Ciências da Educação
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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Dissertação para obtenção do Grau de Mestre em Engenharia Informática
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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Double Degree Masters in Economics Program from Insper and NOVA School of Business and Economics
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The present article is based on the MA thesis of Hou Bowen (Ph.D candidate) and on the presentation made at the ISA World Congress of Sociology held in Yokohama (Japan) on July 2014 at the Session on “Assessing Technologies: Global Patterns of Trust and Distrust” of RC23-Sociology of Science and Technology.
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Remote sensing - the acquisition of information about an object or phenomenon without making physical contact with the object - is applied in a multitude of different areas, ranging from agriculture, forestry, cartography, hydrology, geology, meteorology, aerial traffic control, among many others. Regarding agriculture, an example of application of this information is regarding crop detection, to monitor existing crops easily and help in the region’s strategic planning. In any of these areas, there is always an ongoing search for better methods that allow us to obtain better results. For over forty years, the Landsat program has utilized satellites to collect spectral information from Earth’s surface, creating a historical archive unmatched in quality, detail, coverage, and length. The most recent one was launched on February 11, 2013, having a number of improvements regarding its predecessors. This project aims to compare classification methods in Portugal’s Ribatejo region, specifically regarding crop detection. The state of the art algorithms will be used in this region and their performance will be analyzed.
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Based on the report for the unit “Foresight Analysis Methods” of the PhD program on Technology Assessment in 2013. This unit was supervised by Prof. António Moniz. The paper had meanwhile contributions from the supervisor and Dr. Douglas Robinson.