Deriving Goal Oriented Performance Models By Systematic Experimentation
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Deriving Goal-oriented Performance Models by Systematic Experimentation
Author: Westermann, Dennis
language: en
Publisher: KIT Scientific Publishing
Release Date: 2014-04-10
Performance modelling can require substantial effort when creating and maintaining performance models for software systems that are based on existing software. Therefore, this thesis addresses the challenge of performance prediction in such scenarios. It proposes a novel goal-oriented method for experimental, measurement-based performance modelling. We validated the approach in a number of case studies including standard industry benchmarks as well as a real development scenario at SAP.
Performance Problem Diagnostics by Systematic Experimentation
Author: Wert, Alexander
language: en
Publisher: KIT Scientific Publishing
Release Date: 2018-03-29
In this book, we introduce an automatic, experiment-based approach for performance problem diagnostics in enterprise software systems. The proposed approach systematically searches for root causes of detected performance problems by executing series of systematic performance tests. The presented approach is evaluated by various case studies showing that the presented approach is applicable to a wide range of contexts.
Automated Experiments for Deriving Performance-relevant Properties of Software Execution Environments
Author: Hauck, Michael
language: en
Publisher: KIT Scientific Publishing
Release Date: 2014-02-11
The software execution environment can play a crucial role when analyzing the performance of a software system. In this book, a novel approach for the automated detection of performance-relevant properties of the execution environment is presented. The properties are detected using predefined experiments and integrated into performance prediction tools. The approach is applied to experiments for detecting different CPU, OS, and virtualization properties, and validated in different case studies.