Signals & systems (2nd ed.)
Performance solutions: a practical guide to creating responsive, scalable software
Performance solutions: a practical guide to creating responsive, scalable software
Probability and Statistics with Reliability, Queuing and Computer Science Applications
Probability and Statistics with Reliability, Queuing and Computer Science Applications
Computer
Packaging Predictable Assembly
CD '02 Proceedings of the IFIP/ACM Working Conference on Component Deployment
Automatic component protocol adaptation with the CoConut/J tool suite
Future Generation Computer Systems - Tools for program development and analysis
Parametric Performance Contracts for Software Components with Concurrent Behaviour
Electronic Notes in Theoretical Computer Science (ENTCS)
Predicting the performance of component-based software architectures with different usage profiles
QoSA'07 Proceedings of the Quality of software architectures 3rd international conference on Software architectures, components, and applications
Predicting mean service execution times of software components based on markov models
QoSA'05 Proceedings of the First international conference on Quality of Software Architectures and Software Quality, and Proceedings of the Second International conference on Software Quality
Using qos-contracts to drive architecture-centric self-adaptation
QoSA'10 Proceedings of the 6th international conference on Quality of Software Architectures: research into Practice - Reality and Gaps
Performance prediction of component-based systems
Proceedings of the 2004 international conference on Architecting Systems with Trustworthy Components
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The performance of a software component heavily depends on the environment of the component. As a software component only justifies its investment when deployed in several environments, one can not specify the performance of a component as a constant (e.g., as a single value or distribution of values in its interface). Hence, classical component contracts allowing to state the component's performance as a post-condition, if the environment realises a specific performance stated in the precondition, do not help. This fixed pair of pre- and postcondition do not model that a component can have very different performance figures depending on its context. Instead of that, parametric contracts are needed for specifying the environmental dependency of the component's provided performance. In this paper we discuss the specification of dependencies of external calls for the performance metric response time. We present an approach using parametric contracts to compute the statistical distribution of response time as a discrete distribution in dependency of the distribution of response times of environmental services. We use the Quality of Service Modeling Language (QML) as a syntax for specifying distributions.