theses_hauck.bib

@mastersthesis{hauck2009a,
  abstract = {The performance of a software system is strongly in uenced by the execution environment the software runs in. In the Palladio Component Model (PCM), a domain-specific language for modelling component-based software systems, the execution environment must be modelled explicitly as it is needed for performance predictions. However, the current version of the PCM offers only rudimentary support for hardware resource modelling: For instance, it is not possible to distinguish between read and write accesses to a hard disk resource. This thesis develops an enhancement of the PCM meta-model that allows for better predictions based on more sophisticated resource models. The enhancement includes the support for accessing resources through explicit interfaces with distinct services and the integration of resource controllers in the meta-model. To support modelling of infrastructure components such as application servers, this thesis introduces the separation of business interfaces and interfaces for accessing resources or the execution environment. Existing PCM tools have been adapted to support the simulation of PCM instances based on the enhanced meta-model. Additionally, the adapted meta-model has been successfully evaluated in two case studies to show that the extended meta-model has no side e ects on preexisting predictions and also enables scenarios not supported before, such as the modelling of a Java Virtual Machine which processes higher-level resource demands.},
  address = {Germany},
  author = {Hauck, Michael},
  month = {February},
  school = {University of Karlsruhe (TH)},
  title = {{Extending Performance-Oriented Resource Modelling in the Palladio Component Model}},
  type = {Diploma Thesis},
  url = {http://sdqweb.ipd.uka.de/publications/pdfs/hauck2009a.pdf},
  year = {2009}
}

@phdthesis{hauck2013b,
  abstract = {The software execution environment can play a crucial role when analyzing the performance of a software system. However, detecting execution environment properties and integrating such properties into performance analyses is a manual, error-prone task that requires expert knowledge on the execution environment. In this thesis, a novel approach for detecting performance-relevant properties of the software execution environment is presented. These properties are automatically detected using predefined experiments and integrated into performance prediction tools. Based on a metamodel for experiment specification, the approach is used to design experiments for detecting different CPU, OS scheduling, and virtualization properties. This thesis also includes different case studies which demonstrate the applicability of the approach.},
  author = {Michael Hauck},
  pdf = {http://digbib.ubka.uni-karlsruhe.de/volltexte/documents/2926784},
  school = {Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany},
  title = {Automated Experiments for Deriving Performance-relevant Properties of Software Execution Environments},
  url = {http://digbib.ubka.uni-karlsruhe.de/volltexte/1000037767},
  year = {2013}
}