Derivation of Petri Net Performance Models from UML Specifications of Communications Software

King, Peter J. B.; Pooley, Rob

doi:10.1007/3-540-46429-8_19

Cited by 49 publications

(28 citation statements)

References 8 publications

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“…Accordingly, it is not far fetched to predict that the coming years shall see substantial efforts to extend the UML and the accompanying design methodology towards soft real-time, fault-tolerance, quality of service and the like. First work in this direction has been undertaken, e. g., in [5,9,14,16].…”

Section: Introductionmentioning

confidence: 99%

A Probabilistic Extension of UML Statecharts

Jansen

Hermanns

Katoen

2002

Lecture Notes in Computer Science

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Abstract. This paper introduces means to specify system randomness within UML statecharts, and to verify probabilistic temporal properties over such enhanced statecharts which we call probabilistic UML statecharts. To achieve this, we develop a general recipe to extend a statechart semantics with discrete probability distributions, resulting in Markov decision processes as semantic models. We apply this recipe to the requirements-level UML semantics of [8]. Properties of interest for probabilistic statecharts are expressed in PCTL, a probabilistic variant of CTL for processes that exhibit both non-determinism and probabilities. Verification is performed using the model checker Prism. A model checking example shows the feasibility of the suggested approach.

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Section: Introductionmentioning

confidence: 99%

A Probabilistic Extension of UML Statecharts

Jansen

Hermanns

Katoen

2002

Lecture Notes in Computer Science

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“…Some authors propose the translation of UML models into stochastic Petri net models or stochastic process algebra specifications [38,29,10] in order to perform quantitative evaluation of software systems. However, the more mature approaches based on formal specification languages such as STPN and SPA do not combine UML with SPA or STPN.…”

Section: Methodologies Based On Formal Specification Languagesmentioning

confidence: 99%

Integrating Performance Modeling in the Software Development Process

Balsamo

Simeoni

2004

Radical Innovations of Software and Systems Engineering in the Future

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Abstract. We discuss the integration of performance modeling and analysis in the software development process. Various approaches have been recently defined to integrate performance models and specification languages and models to derive or validate non-functional properties of a software system. Such integration of quantitative performance analysis should provide feedback easily understandable by the software designer and system developers. A framework that allows the combination of different performance modeling techniques and methods, defined at different levels of abstraction, should better support performance analysis and validation of complex and heterogeneous software systems during the software development process.

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“…This approach is based on client/server software performance evaluation (CLISSPE). In King and Pooley (2000) the authors show an example how to generate stochastic timed Petri net models from UML diagrams. Finally, presents an example of the derivation of a performance model from an object-oriented design model.…”

Section: Performance Assessment In Ambient Intelligence (Paai)mentioning

confidence: 99%

Performance assessment of intelligent distributed systems through software performance ontology engineering (SPOE)

et al. 2007

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In the computer science community there is a growing interest in the field of Ambient Intelligent Systems. This systems surround their human users with computing and networking technology unobtrusively embedded in their environment. This technology is aimed to provide the users with useful information and to take action to make the environment more convenient for them. As the number of users increases the resources that make Ambient Intelligence possible can be easily saturated making the system unstable and projecting an image of poor QoS to the users. The main goal of this paper is to provide the means for the Ambient Intelligent Systems to monitor themselves and take corrective action automatically if performance starts to drop. Our approach uses a Performance Ontology that structures the knowledge about Software Performance Engineering, and a reasoning engine that acts like an expert system with the Performance Ontology as its foundation. The case study at the end shows the applicability of the developed techniques.

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Derivation of Petri Net Performance Models from UML Specifications of Communications Software

Cited by 49 publications

References 8 publications

A Probabilistic Extension of UML Statecharts

A Probabilistic Extension of UML Statecharts

Integrating Performance Modeling in the Software Development Process

Performance assessment of intelligent distributed systems through software performance ontology engineering (SPOE)

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