Software engineering and performance: a roadmap
Proceedings of the Conference on The Future of Software Engineering
Performance Modeling of Heterogeneous Distributed Applications
MASCOTS '96 Proceedings of the 4th International Workshop on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems
Measuring End-to-End Performance of CORBA Applications using a Generic Instrumentation Approach
ISCC '02 Proceedings of the Seventh International Symposium on Computers and Communications (ISCC'02)
Queueing Networks and Markov Chains
Queueing Networks and Markov Chains
A Software Performance Engineering Tool based on the UML-SPT
QEST '05 Proceedings of the Second International Conference on the Quantitative Evaluation of Systems
Performance modeling and prediction of enterprise JavaBeans with layered queuing network templates
SAVCBS '05 Proceedings of the 2005 conference on Specification and verification of component-based systems
Building Java program analysis tools using Javana
Companion to the 21st ACM SIGPLAN symposium on Object-oriented programming systems, languages, and applications
SOA monitoring based on a formal workflow model with constraints
Proceedings of the 1st international workshop on Quality of service-oriented software systems
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Problems such as inconsistent or erroneous instrumentation often plague applications whose source code ismanually instrumented during the implementation phase. Integrating performance instrumentation capabilities into theModel Driven Software Development (MDSD) process would greatly assist software engineers who do not have detailed knowledge of source code instrumentation technologies. This paper presents an approach that offers instrumentation support to software designers and developers. A collection of instrumentation patterns is defined to represent typical instrumentation scenarios for distributed applications.AUML profile derived from these patterns is then used to annotate UML models. Based on suitable code generation templates, the annotated models are transformed into instrumented source code for different instrumentation APIs. A prototypical implementation, including an adaptation toWeb services, was evaluated in a lab environment.