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.

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.

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.

Die modellbasierte Performancevorhersage ist ein bekanntes Konzept zur Gewährleistung der Softwarequalität. Derzeitige Ansätze basieren auf einem Modell mit einer Metrik, was zu ungenauen Vorhersagen für moderne Architekturen führt. In dieser Arbeit wird ein Multi-Strategie-Ansatz zur Erweiterung von Performancevorhersagemodellen zur Unterstützung von Multicore-Architekturen vorgestellt, in Palladio implementiert und dadurch die Genauigkeit der Vorhersage deutlich verbessert. - Model-based performance prediction is a well-known concept to ensure the quality of software. Current approaches are based on a single-metric model, which leads to inaccurate predictions for modern architectures. This thesis presents a multi-strategies approach to extend performance prediction models to support multicore architectures. We implemented the strategies into Palladio and significantly increased the performance prediction power.

This work developed an automatic approach for the assessment of software reliability which is both theoretical sound and practical. The developed approach extends and combines theoretical sound approaches in a novel manner to systematically reduce the overhead of reliability assessment.

The quality of enterprise software applications plays a crucial role for the satisfaction of the users and the economic success of the enterprises. Software applications with unsatisfying performance and scalability are perceived by its users as low in quality, as less interesting and less attractive, and cause frustration when preventing the users from attaining their goals. This book proposes an approach for a recommendation system that enables developers who are novices in software perform.