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Auflistung nach Autor:in "Carr, Leslie"

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  • Zeitschriftenartikel
    Combining Kieker with Gephi for Performance Analysis and Interactive Trace Visualization
    (Softwaretechnik-Trends Band 35, Heft 3, 2015) Zirkelbach, Christian; Hasselbring, Wilhelm; Carr, Leslie
    Performing an analysis of established software usually is challenging. Based on reverse engineering through dynamic analysis, it is possible to perform a software performance analysis, in order to detect performance bottlenecks or issues. This process is often divided into two consecutive tasks. The first task concerns monitoring the software, and the second task covers analysing and visualizing the results. In this paper, we report on our performance analysis of the Perl-based open repository software EPrints, which has now been continuously developed for more than fifteen years. We analyse and evaluate the software using Kieker, and employ the visualization tool Gephi for performance analysis and interactive trace visualization. This allows us, in collaboration with the EPrints development team, to reverse engineer their software EPrints, to give new and unexpected insights, and to detect potential bottlenecks.
  • Zeitschriftenartikel
    From FAIR research data toward FAIR and open research software
    (it - Information Technology: Vol. 62, No. 1, 2020) Hasselbring, Wilhelm; Carr, Leslie; Hettrick, Simon; Packer, Heather; Tiropanis, Thanassis
    The Open Science agenda holds that science advances faster when we can build on existing results. Therefore, research data must be FAIR (Findable, Accessible, Interoperable, and Reusable) in order to advance the findability, reproducibility and reuse of research results. Besides the research data, all the processing steps on these data – as basis of scientific publications – have to be available, too. For good scientific practice, the resulting research software should be both open and adhere to the FAIR principles to allow full repeatability, reproducibility, and reuse. As compared to research data, research software should be both archived for reproducibility and actively maintained for reusability. The FAIR data principles do not require openness, but research software should be open source software. Established open source software licenses provide sufficient licensing options, such that it should be the rare exception to keep research software closed. We review and analyze the current state in this area in order to give recommendations for making research software FAIR and open.