1,686 research outputs found

    PROGRAM SLICING TECHNIQUES AND ITS APPLICATIONS

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    Program understanding is an important aspect in Software Maintenance and Reengineering. Understanding the program is related to execution behaviour and relationship of variable involved in the program. The task of finding all statements in a program that directly or indirectly influence the value for an occurrence of a variable gives the set of statements that can affect the value of a variable at some point in a program is called a program slice. Program slicing is a technique for extracting parts of computer programs by tracing the programs’ control and data flow related to some data item. This technique is applicable in various areas such as debugging, program comprehension and understanding, program integration, cohesion measurement, re-engineering, maintenance, testing where it is useful to be able to focus on relevant parts of large programs. This paper focuses on the various slicing techniques (not limited to) like static slicing, quasi static slicing, dynamic slicing and conditional slicing. This paper also includes various methods in performing the slicing like forward slicing, backward slicing, syntactic slicing and semantic slicing. The slicing of a program is carried out using Java which is a object oriented programming language

    Processo de depuração depois do teste: definição e análise.

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    O objetivo da realização deste trabalho foi analisar em detalhes o processo de depuração que ocorre depois da atividade de teste. Por tanto, vários processos de depuração de software foram analisados. Baseado nessa análise foi definido um processo de Depuração depois do teste (DDT) que enfativa os seguintes aspectos: identificação, avaliação e refinamento sucessivo de sintomas internos até a localização do defeito; e tipo de informação de teste utilizada. Várias técnicas de depuração foram então avaliadas em termos de mecanismos de apoio ao processo DDT e quanto a sua escabilidade para programas reais. Dessa avaliação, observou-se que os resultados do teste sistemático de software, quando utilizado na depuração, resultam em técnicas de baixo custo e com maiores perspectivas de escabilidade para programas reais. Infelizmente, esses resultados têm sido utilizados apenas para apoiar um dos aspectos do processo DDT- identificação de sintomas internos. Essa observação motiva a definição de estratégias de depuração que utilizem, de maneira eficaz e eficiente, as informações de teste na avaliação e no refinamento de sintomas internos.bitstream/CNPTIA/9957/1/bolpesq5.pdfAcesso em: 28 maio 2008

    Glossary of Software Engineering Laboratory terms

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    A glossary of terms used in the Software Engineering Laboratory (SEL) is given. The terms are defined within the context of the software development environment for flight dynamics at the Goddard Space Flight Center. A concise reference for clarifying the language employed in SEL documents and data collection forms is given. Basic software engineering concepts are explained and standard definitions for use by SEL personnel are established

    Glossary of software engineering laboratory terms

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    A glossary of terms used in the Software Engineering Laboratory (SEL) is presented. The terms are defined within the context of the software development environment for flight dynamics at Goddard Space Flight Center. A concise reference for clarifying and understanding the language employed in SEL documents and data collection forms is provided

    NASA space station automation: AI-based technology review

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    Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

    The exploitation of parallelism on shared memory multiprocessors

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    PhD ThesisWith the arrival of many general purpose shared memory multiple processor (multiprocessor) computers into the commercial arena during the mid-1980's, a rift has opened between the raw processing power offered by the emerging hardware and the relative inability of its operating software to effectively deliver this power to potential users. This rift stems from the fact that, currently, no computational model with the capability to elegantly express parallel activity is mature enough to be universally accepted, and used as the basis for programming languages to exploit the parallelism that multiprocessors offer. To add to this, there is a lack of software tools to assist programmers in the processes of designing and debugging parallel programs. Although much research has been done in the field of programming languages, no undisputed candidate for the most appropriate language for programming shared memory multiprocessors has yet been found. This thesis examines why this state of affairs has arisen and proposes programming language constructs, together with a programming methodology and environment, to close the ever widening hardware to software gap. The novel programming constructs described in this thesis are intended for use in imperative languages even though they make use of the synchronisation inherent in the dataflow model by using the semantics of single assignment when operating on shared data, so giving rise to the term shared values. As there are several distinct parallel programming paradigms, matching flavours of shared value are developed to permit the concise expression of these paradigms.The Science and Engineering Research Council

    Fourth Conference on Artificial Intelligence for Space Applications

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    Proceedings of a conference held in Huntsville, Alabama, on November 15-16, 1988. The Fourth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: space applications of expert systems in fault diagnostics, in telemetry monitoring and data collection, in design and systems integration; and in planning and scheduling; knowledge representation, capture, verification, and management; robotics and vision; adaptive learning; and automatic programming
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