Logo des Repositoriums

Auflistung nach Autor:in "Eismann, Simon"

1 - 5 von 5
  • Zeitschriftenartikel
    Automated Transformation of Descartes Modeling Language to Palladio Component Model
    (Softwaretechnik-Trends Band 35, Heft 3, 2015) Walter, Jürgen; Eismann, Simon; Hildebrandt, Adrian
    Model-based performance predictions and reconfigurations enable optimizing resource efficiency while ensuring that Quality-of-Service demands are met in today’s complex ITsystems. The Descartes Modeling Language (DML) and the Palladio Component Model (PCM) are two architectural performance modeling formalisms applied in this context. This paper compares DML to PCM concerning similarities, differences and semantic gaps. Based on this, we propose a mapping from DML to PCM for which we implemented a tool realizing an automated transformation.
  • Konferenzbeitrag
    On Learning Parametric Dependencies from Monitoring Data
    (Softwaretechnik-Trends Band 39, Heft 4, 2019) Grohmann, Johannes; Eismann, Simon; Kounev, Samuel
    A common approach to predict system performance are so-called architectural performance models. In these models, parametric dependencies describe the relation between the input parameters of a component and its performance properties and therefore significantly increase the model expressiveness. However, manually modeling parametric dependencies is often infeasible in practice. Existing automated extraction approaches require either application source code or dedicated performance tests, which are not always available. We therefore introduced one approach for identification and one for characterization of parametric dependencies, solely based on run-time monitoring data. In this paper, we propose our idea on combining both techniques in order to create a holistic approach for the identification and characterization of parametric dependencies. Furthermore, we discuss challenges we are currently facing and potential ideas on how to overcome them.
  • Zeitschriftenartikel
    PAVO: A Framework for the Visualization of Performance Analyses Results
    (Softwaretechnik-Trends Band 36, Heft 4, 2016) Walter, Jürgen; König, Maximilian; Eismann, Simon; Kounev, Samuel
    Awareness of application performance can be derived through various quantitative analyses, model-based and measurement-based approaches. A suitable visualization supports the understanding of application performance. Usually, analysis tools include a tool specific visualization or no visualization at all. In this paper we proposed to decouple the result visualization from the analysis approach. We present the Performance VisualizatiOn (PAVO) framework which provides result visualization tailored to a given performance analysis result. To show benefits and usability of PAVO, we present our integration in Descartes Query Language (DQL).
  • Zeitschriftenartikel
    Providing Model-Extraction-as-a-Service for Architectural Performance Models
    (Softwaretechnik-Trends Band 37, Heft 3, 2017) Walter, Jürgen; Eismann, Simon; Reed, Nikolai; Kounev,Samuel
    Architectural performance models can be leveraged to explore performance properties of software systems during design-time and run-time. We see a reluctance from industry to adopt model-based analysis approaches due to the required expertise and modeling effort. Building models from scratch in an editor does not scale for medium and large scale systems in an industrial context. Existing open-source performance model extraction approaches imply significant initial efforts which might be challenging for layman users. To simplify usage, we provide the extraction of architectural performance models based on application monitoring traces as a web service. Model-Extraction-as-a-Service (MEaaS) solves the usability problem and lowers the initial effort of applying model-based analysis approaches.
  • Konferenzbeitrag
    TeaStore: A Micro-Service Reference Application for Benchmarking, Modeling and Resource Management Research
    (Software Engineering and Software Management 2019, 2019) von Kistowski, Jóakim; Eismann, Simon; Schmitt, Norbert; Bauer, André; Grohmann, Johannes; Kounev, Samuel