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Auflistung nach Autor:in "Schmid, Larissa"

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  • Konferenzbeitrag
    Continuing to Catch Up with State of the Art Continuous Integration Pipelines in Palladio – The Experience Report Strikes Back
    (Softwaretechnik-Trends Band 43, Heft 4, 2023) Alber, Lucas; Boltz, Nicolas; Schmid, Larissa
    The Palladio organization comprises over 50 software artifacts and is actively developed by over 32 members. This research paper presents a case study on the migration from Jenkins to GitHub Actions for automated builds in the development workflow for Palladio. The transition has yielded significant improvements in continuous integration, review processes, and deployment efficiency. The adoption of GitHub Actions’ modular and reusable workflows has further optimized our build pipeline, resulting in enhanced maintainability and reduced redundancy. Additionally, by leveraging dependency analysis, we applied the idea of incremental builds to the whole organization and automated the generation of build workflows, leading to improved resource utilization and an average speed-up in build times of 11.7. This study highlights the benefits of embracing GitHub Actions and provides valuable insights for development teams seeking to streamline their build processes.
  • Konferenzbeitrag
    Performance Modelling of Message-Oriented Middleware with Priority Queues
    (Softwaretechnik-Trends Band 40, Heft 3, 2020) Singh, Snigdha; Schmid, Larissa; Koziolek, Anne
    Message-Oriented Middleware (MOM) with priority queues reduces the latency of critical events. In general, MOM uses a FIFO queuing methodology. But, different application scenarios require certain critical events with higher priority to be served earlier over low-priority events, so that the subscriber of the event consumes the high-priority event with less delay. In the context of the Palladio Component Model (PCM), MOM-based systems have been modelled considering message queue length and latency as metrics for performance prediction and simulation. However, the approaches did not consider modelling MOM with priority queues and their impact on performance. We will first, discuss the existing approaches in PCM which support performance prediction for MOM-based systems and then propose how they can be extended to support performance predictions for MOM with priority queuing. We will then conclude which approach is best suited to extend by assessing their capabilities to predict performance metrics relevant for priority queuing, especially the delay of individual events at the subscriber end.