1,040,603 research outputs found

    Model-driven performance evaluation for service engineering

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    Service engineering and service-oriented architecture as an integration and platform technology is a recent approach to software systems integration. Software quality aspects such as performance are of central importance for the integration of heterogeneous, distributed service-based systems. Empirical performance evaluation is a process of measuring and calculating performance metrics of the implemented software. We present an approach for the empirical, model-based performance evaluation of services and service compositions in the context of model-driven service engineering. Temporal databases theory is utilised for the empirical performance evaluation of model-driven developed service systems

    Quality-aware model-driven service engineering

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    Service engineering and service-oriented architecture as an integration and platform technology is a recent approach to software systems integration. Quality aspects ranging from interoperability to maintainability to performance are of central importance for the integration of heterogeneous, distributed service-based systems. Architecture models can substantially influence quality attributes of the implemented software systems. Besides the benefits of explicit architectures on maintainability and reuse, architectural constraints such as styles, reference architectures and architectural patterns can influence observable software properties such as performance. Empirical performance evaluation is a process of measuring and evaluating the performance of implemented software. We present an approach for addressing the quality of services and service-based systems at the model-level in the context of model-driven service engineering. The focus on architecture-level models is a consequence of the black-box character of services

    Proof-of-concept engineering workflow demonstrator

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    When Microsoft needed a proof-of-concept implementation of bespoke engineering workflow software for their customer, BAE Systems, it called on the software engineering skills and experience of the Microsoft Institute for High Performance Computing. BAE Systems was looking into converting their in-house SOLAR software suite to run on the MS Compute Cluster Server product with 64-bit MPI support in conjunction with an extended Windows Workflow environment for use by their engineer

    Report from GI-Dagstuhl Seminar 16394: Software Performance Engineering in the DevOps World

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    This report documents the program and the outcomes of GI-Dagstuhl Seminar 16394 "Software Performance Engineering in the DevOps World". The seminar addressed the problem of performance-aware DevOps. Both, DevOps and performance engineering have been growing trends over the past one to two years, in no small part due to the rise in importance of identifying performance anomalies in the operations (Ops) of cloud and big data systems and feeding these back to the development (Dev). However, so far, the research community has treated software engineering, performance engineering, and cloud computing mostly as individual research areas. We aimed to identify cross-community collaboration, and to set the path for long-lasting collaborations towards performance-aware DevOps. The main goal of the seminar was to bring together young researchers (PhD students in a later stage of their PhD, as well as PostDocs or Junior Professors) in the areas of (i) software engineering, (ii) performance engineering, and (iii) cloud computing and big data to present their current research projects, to exchange experience and expertise, to discuss research challenges, and to develop ideas for future collaborations

    Advanced technologies for Mission Control Centers

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    Advance technologies for Mission Control Centers are presented in the form of the viewgraphs. The following subject areas are covered: technology needs; current technology efforts at GSFC (human-machine interface development, object oriented software development, expert systems, knowledge-based software engineering environments, and high performance VLSI telemetry systems); and test beds

    Software Engineering Laboratory Ada performance study: Results and implications

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    The SEL is an organization sponsored by NASA/GSFC to investigate the effectiveness of software engineering technologies applied to the development of applications software. The SEL was created in 1977 and has three organizational members: NASA/GSFC, Systems Development Branch; The University of Maryland, Computer Sciences Department; and Computer Sciences Corporation, Systems Development Operation. The goals of the SEL are as follows: (1) to understand the software development process in the GSFC environments; (2) to measure the effect of various methodologies, tools, and models on this process; and (3) to identify and then to apply successful development practices. The activities, findings, and recommendations of the SEL are recorded in the Software Engineering Laboratory Series, a continuing series of reports that include the Ada Performance Study Report. This paper describes the background of Ada in the Flight Dynamics Division (FDD), the objectives and scope of the Ada Performance Study, the measurement approach used, the performance tests performed, the major test results, and the implications for future FDD Ada development efforts

    Measurement and Prediction of Software Performance by Models

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    Software Performance Engineering (SPE) provides a systematic, quantitative approach to constructing software systems that meet performance objectives. It prescribes ways to build performance into new systems rather than try to fix them later. Performance is a pervasive quality of software systems; everything affects it, from the software itself to all underlying layers, such as operating system, middleware, hardware, communication networks, etc. Software Perfor - mance Engineering encompasses efforts to describe and improve performance, with two distinct approaches: an earlycycle predictive model-based approach, and a late-cycle measurement-based approach. Current progress and future trends within these two approaches are described, with a tendency (and a need) for them to converge, in order to cover the entire development cycle

    Digital signal processing: the impact of convergence on education, society and design flow

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    Design and development of real-time, memory and processor hungry digital signal processing systems has for decades been accomplished on general-purpose microprocessors. Increasing needs for high-performance DSP systems made these microprocessors unattractive for such implementations. Various attempts to improve the performance of these systems resulted in the use of dedicated digital signal processing devices like DSP processors and the former heavyweight champion of electronics design – Application Specific Integrated Circuits. The advent of RAM-based Field Programmable Gate Arrays has changed the DSP design flow. Software algorithmic designers can now take their DSP algorithms right from inception to hardware implementation, thanks to the increasing availability of software/hardware design flow or hardware/software co-design. This has led to a demand in the industry for graduates with good skills in both Electrical Engineering and Computer Science. This paper evaluates the impact of technology on DSP-based designs, hardware design languages, and how graduate/undergraduate courses have changed to suit this transition

    Creating Responsive Information Systems with the Help of SSADM

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    In this paper, a program for a research is outlined. Firstly, the concept of responsive information systems is defined and then the notion of the capacity planning and software performance engineering is clarified. Secondly, the purpose of the proposed methodology of capacity planning, the interface to information systems analysis and development methodologies (SSADM), the advantage of knowledge-based approach is discussed. The interfaces to CASE tools more precisely to data dictionaries or repositories (IRDS) are examined in the context of a certain systems analysis and design methodology (e.g. SSADM)
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