Saturday, 21 October 2017

DynamicSpotter - A framework for measurement-based, automatic detection of software performance problems

Description

DynamicSpotter is a framework for measurement-based, automatic detection of software performance problems in Java-based enterprise software systems. DynamicSpotter combines the concepts of software performance anti-patterns with systematic experimentation.

DynamicSpotter utilizes the concept of hierarchically structuring performance problems in order to automate the search for recurring performance problems by systematically executing measurement experiments. DynamicSpotter takes a hierarchy of symptoms, performance problem and root causes as input. For each node of that hierarchy, performance experts define a heuristic responsible to decide on the existence of the corresponding problem. To this end, a heuristic executes a series of experiments, observes certain performance metrics and analyzes them to make a decision. Traversing the problem hierarchy and applying corresponding heuristics for each performance problem of the hierarchy, DynamicSpotter generates a detection result report. The report states for each node in the hierarchy whether the corresponding problem exists in the SUT and, where appropriate, points to the root cause and location in the SUT of a detected problem.

Requirements
  • Java 6 or higher
  • Eclipse Kepler or higher
Contributor(s)
  • Alexander Wert,
  • Christoph Heger,
  • Roozbeh Farahbod,
  • Denis Knöpfle,
  • Peter Merkert,
  • Marius Oehler,
  • Henning Schulz
Maintainer(s)
  • Dr.-Ing. Alexander Wert, alexander.wert(at)novatec-gmbh.de

    NovaTec Consulting GmbH
    Dieselstraße 18/1
    Leinfelden-Echterdingen, Germany
Version
  • 1.0
Download
License
  • Apache License, Version 2.0
Website
Publications/ Projects using the tool
  • A. Wert, Performance problem diagnostics by systematic experimentation, in: Proc. WCOP. ACM, 2013, pp. 1-6.
  • A. Wert, J. Happe, and L. Happe, Supporting swift reaction: automatically uncovering performance problems by systematic experiments, in: Proc. ICSE. IEEE Press, 2013, pp. 552-561.
  • A. Wert, M. Oehler, C. Heger, and R. Farahbod, Automatic Detection of Performance Anti-patterns in Inter-component Communications, in: Proceedings of the 10th International Conference on Quality of Software Architecture, ser. QoSA '14, 2014.
  • A. Wert, DynamicSpotter: Automatic, Experiment-based Diagnostics of Performance Problems, in: Proceedings of the 6th ACM/SPEC International Conference on Performance Engineering (ICPE’15), pp 105-106
  • A. Wert, Performance problem diagnostics by systematic experimentation, PhD Thesis, Karlsruhe Institute of Technology, 2015