Putting Performance Engineering into Model-Driven Engineering: Model-Driven Performance Engineering

Fritzsche, Mathias; Johannes, Jendrik

doi:10.1007/978-3-540-69073-3_18

Cited by 21 publications

(14 citation statements)

References 11 publications

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“…The proposed approaches address the integration of performance analysis at early stages of the development process. Several works [23,41] review model-based performance prediction approaches. These studies focus on the importance of conducting performance analysis at different stages throughout the software development cycle.…”

Section: Chapter 4 Related Workmentioning

confidence: 99%

Performance prediction upon toolchain migration in model-based software

Ketata

Moreno

Fischmeister

et al. 2015

2015 ACM/IEEE 18th International Conference on Model Driven Engineering Languages and Systems (MODELS)

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Changing the development environment can have severe impacts on the system behavior such as the execution-time performance. Since it can be costly to migrate a software application, engineers would like to predict the performance parameters of the application under the new environment with as little effort as possible.In this work, we concentrate on model-driven development and provide a methodology to estimate the execution-time performance of application models under different toolchains. Our approach has low cost compared to the migration effort of an entire application. As part of the approach, we provide methods for characterizing model-driven applications, an algorithm for generating application-specific microbenchmarks, and results on using different methods for estimating the performance. In the work, we focus on SCADE as the development toolchain and use a Cruise Control and a Water Level application as case studies to confirm the technical feasibility and viability of our technique.iii Acknowledgements I would like to thank my supervisor Prof. Sebastian Fischmeister for his continuous guidance, insights and support throughout my master. Thank you for giving me the opportunity to work flexibly and for always finding time for me. Your collaboration made the achievement of this work possible.I would also like to thank Carlos Moreno for his fruitful discussions, continuous assistance, and advice. Thank you for being patient and motivating my research.I would like to thank Prof. Krzysztof Czarnecki and Prof. Werner M. Dietl for reading and reviewing my thesis.For the discussions on constraint solvers and model-based applications, and reviewing my work, I would like to thank Jimmy Liang.To my family, thanks for your love and support all these years.To my friends, thanks for making my studies at Waterloo full of joyful moments and great souvenirs.

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Section: Chapter 4 Related Workmentioning

confidence: 99%

Performance prediction upon toolchain migration in model-based software

Ketata

Moreno

Fischmeister

et al. 2015

2015 ACM/IEEE 18th International Conference on Model Driven Engineering Languages and Systems (MODELS)

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“…The concept of Model-Driven Performance Engineering was introduced by Frietzsche and Johannes in [6] and is defined as a process combining MDE and performance engineering: structural and behavioral models can be annotated with performance information and performance analysis can be applied at the different stages of refinement of the MDE process. In this context, several works have been proposed, typically considering UML design models that are transformed into a LQN or queueing network performance model, like, for example, [7,4] where XLST and ATL rules are used for the transformation, respectively.…”

Section: Related Workmentioning

confidence: 99%

“…Being able to correctly size the resources needed by a Web application to its incoming workload is the ultimate goal of performance engineering [4,6]. For a company, both over-and under-provisioning turn into revenue loss: in the former case because of higher than needed operational costs, in the latter case because the Quality of Service is below clients' expectations.…”

Section: Introductionmentioning

confidence: 99%

Model-Driven Web Engineering Performance Prediction with Layered Queue Networks

Gambi

Toffetti

Comai

2010

Current Trends in Web Engineering

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Abstract. This position paper describes an approach to predict the performances of a Web application already in the early stages of application development. It leverages the wealth of information of MDWE solutions to automatically obtain accurate representations of the running application in terms of layered queue networks (LQNs), i.e., analytical models simulating the behavior of the system and computing the performances mathematically. In particular, the paper discusses how a MDWE methodology can be exploited to generate such performance models and presents a proof of concept example.

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“…In our previous work [1], we proposed ModelDriven Performance Engineering (MDPE) for early performance feedback. The process supports earlier initial performance feedback with minimal effort as well as maximal performance feedback with extended (but still cost-efficient) effort by utilization of Model Driven Engineering (MDE) concepts.…”

Section: Introductionmentioning

confidence: 99%

“…We identified the requirement of a synchronization mechanism, between the development models 1 and performance analysis models, in order to adequately integrate the performance analysis results into the development process. This requirement is extended here with the notion of providing performance related decision support based on analysed performance view models.…”

Section: Introductionmentioning

confidence: 99%