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Auflistung nach Schlagwort "metrics"

1 - 5 von 5
  • Konferenzbeitrag
    An Architectural Template for Parallel Loops and Sections
    (Softwaretechnik-Trends Band 39, Heft 3, 2019) Frank, Markus; Hakamian, Alireza
    The Palladio Component Model uses UML-like diagrams to specify architectural software designs, which are used for early design-time analyses of software performance metrics. As a current drawback of the PCM, it does not support the specification of massive parallel software behaviour like OpenMP parallel loops. For Software Performance Engineers this results in complex modelling workarounds, or it is not possible to model the software’s behaviour at all, which results in inaccurate analyses and semantic discrepancies. In this paper, we present a light-weight PCM metamodel extension, allowing SPEs to easily annotate parallel sections (similar to OpenMP) in their software specifications. This significantly reduces the modelling effort through automation.
  • Konferenzbeitrag
    Collaborative software visualization with SEE
    (Softwaretechnik-Trends Band 43, Heft 2, 2023) Behnke, William; Kuß, Hannes Lennart
    SEE is a software engineering tool for visualizing software metrics based on the code-cities metaphor. It assists distributed teams in analyzing software collaboratively by offering multi-user functionality (including a voice chat), that allows team members to communicate naturally while investigating software. The tool utilizes graphs supplied in the Graph eXchange Language (GXL) format to represent software data, and allows users—among other things—to compare the current architecture with the original plan and to track changes of a software over time. One of our long-term goals is to enhance communication and collaboration among team members, to bridge spatial gaps, and to facilitate the understanding of software in (spatially separated) teams.
  • Konferenzbeitrag
    FAIR is not enough -- A Metrics Framework to ensure Data Quality through Data Preparation
    (BTW 2023, 2023) Restat, Valerie; Klettke, Meike; Störl, Uta
    Data-driven systems and machine learning-based decisions are becoming increasingly important and are having an impact on our everyday lives. The prerequisite for this is good data quality, which must be ensured by preprocessing the data. For domain experts, however, the following difficulties arise: On the one hand, they have to choose from a multitude of different tools and algorithms. On the other hand, there is no uniform evaluation method for data quality. For this reason, we present the design of a framework of metrics that allows for a flexible evaluation of data quality and data preparation results.
  • Konferenzbeitrag
    Identifying Domain-Based Cyclic Dependencies in Microservice APIs Using Source Code Detectors
    (Software Engineering 2022, 2022) Genfer, Patric; Zdun, Uwe
    Isolation, autonomy, and loose coupling are critical success factors of microservice architectures, but unfortunately, systems tend to become strongly coupled over time and sometimes even exhibiting cyclic communication chains. These cycles can even manifest on a conceptual or domain level, making them hard to track for algorithms that rely solely on static analysis. Accordingly, previous attempts to detect cycles either focused on synchronous communication or had to collect additional runtime data, which can be costly and time-consuming. We suggest a novel approach for identifying and evaluating domain-based cyclic dependencies in microservice systems based on modular, reusable source code detectors. Based on the architecture model reconstructed by our detectors, we derived a set of architectural metrics for identifying and classifying domain-based cyclical dependencies. By conducting two case studies on open-source microservice architectures, we validated the feasibility and applicability of our approach.
  • Konferenzbeitrag
    Kennzahlen kooperativer Arbeitsbereiche
    (i-com: Vol. 13, No. 2, 2014) Prinz, Wolfgang; Jeners, Nils
    The paper presents metrics for shared workspaces, based on the analysis of user activities in the shared workspace system BSCW. We propose metrics to compare the activity, productivity and cooperativity of users in different shared workspaces. Our analysis indicates that the metrics allow for a mapping of workspaces to a usage intention as well as a benchmark between different user groups. Furthermore we observed the Pareto principle known from other statistical evaluations also in the ratio between active and passive users of a workspace. Additionally our research indicates the distribution ratio of information within a shared workspaces.