Parametric performance completions for model-driven performance prediction
Performance Evaluation
Information and Software Technology
Ginpex: deriving performance-relevant infrastructure properties through goal-oriented experiments
Proceedings of the joint ACM SIGSOFT conference -- QoSA and ACM SIGSOFT symposium -- ISARCS on Quality of software architectures -- QoSA and architecting critical systems -- ISARCS
Validating model-driven performance predictions on random software systems
QoSA'10 Proceedings of the 6th international conference on Quality of Software Architectures: research into Practice - Reality and Gaps
Model transformations in non-functional analysis
SFM'12 Proceedings of the 12th international conference on Formal Methods for the Design of Computer, Communication, and Software Systems: formal methods for model-driven engineering
Performance analysis of self-adaptive systems for requirements validation at design-time
Proceedings of the 9th international ACM Sigsoft conference on Quality of software architectures
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Early, model-based performance predictions help to understand the consequences of design decisions on the performance of the resulting system before the system's implementation becomes available. While this helps reducing the costs for redesigning systems not meeting their extra-functional requirements, performance prediction models have to abstract from the full complexity of modern hard- and software environments potentially leading to imprecise predictions. As a solution, the construction and execution of prototypes on the target execution environment gives early insights in the behaviour of the system under realistic conditions. In literature several approaches exist to generate prototypes from models which either generate code skeletons or require detailed models for the prototype. In this paper, we present an approach which aims at automated generation of a performance prototype based solely on a design model with performance annotations. For the concrete realisation, we used the Palladio Component Model (PCM), which is a component-based architecture modelling language supporting early performance analyses. For a typical three-tier business application, the resulting Java EE code shows how the prototype can be used to evaluate the influence of complex parts of the execution environment like memory interactions or the operating system's scheduler.