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Steffen Becker

Bio: Steffen Becker is an academic researcher from University of Stuttgart. The author has contributed to research in topics: Component (UML) & Software system. The author has an hindex of 29, co-authored 132 publications receiving 3230 citations. Previous affiliations of Steffen Becker include Center for Information Technology & Chemnitz University of Technology.


Papers
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Journal ArticleDOI
TL;DR: The Palladio component model (PCM) is used to specify component-based software architectures in a parametric way to enable the prediction of extra-functional properties, and the resulting prediction accuracy is sufficient to support the evaluation of architectural design decisions.

749 citations

Proceedings ArticleDOI
05 Feb 2007
TL;DR: This paper uses the Palladio Component Model (PCM) to specify component-based software architectures in a parametric way and presents a model and a simulation tool based on it, which can be sufficient to support the evaluation of architectural design decisions.
Abstract: One aim of component-based software engineering (CBSE) is to enable the prediction of extra-functional properties, such as performance and reliability, utilising a well-defined composition theory. Nowadays, such theories and their accompanying prediction methods are still in a maturation stage. Several factors influencing extra-functional properties need additional research to be understood. A special problem in CBSE stems from its specific development process: Software components should be specified and implemented independent from their later context to enable reuse. Thus, extra-functional properties of components need to be specified in a parametric way to take different influence factors like the hardware platform or the usage profile into account. In our approach, we use the Palladio Component Model (PCM) to specify component-based software architectures in a parametric way. This model offers direct support of the CBSE development process by dividing the model creation among the developer roles. In this paper, we present our model and a simulation tool based on it, which is capable of making performance predictions. Within a case study, we show that the resulting prediction accuracy can be sufficient to support the evaluation of architectural design decisions.

207 citations

Proceedings ArticleDOI
28 Jan 2010
TL;DR: This work proposes an automated approach to search the design space for good solutions by applying a multi-criteria genetic algorithm to software architectures modelled with the Palladio Component Model and can be extended to other quantitative quality criteria of software architectures.
Abstract: Quantitative prediction of quality properties (i.e. extra-functional properties such as performance, reliability, and cost) of software architectures during design supports a systematic software engineering approach. Designing architectures that exhibit a good trade-off between multiple quality criteria is hard, because even after a functional design has been created, many remaining degrees of freedom in the software architecture span a large, discontinuous design space. In current practice, software architects try to find solutions manually, which is time-consuming, can be error-prone and can lead to suboptimal designs. We propose an automated approach to search the design space for good solutions. Starting with a given initial architectural model, the approach iteratively modifies and evaluates architectural models. Our approach applies a multi-criteria genetic algorithm to software architectures modelled with the Palladio Component Model. It supports quantitative performance, reliability, and cost prediction and can be extended to other quantitative quality criteria of software architectures. We validate the applicability of our approach by applying it to an architecture model of a component-based business information system and analyse its quality criteria trade-offs by automatically investigating more than 1200 alternative design candidates.

198 citations

Book
21 Oct 2016
TL;DR: This book presents a new, quantitative architecture simulation approach to software design, Palladio, which allows software engineers to model quality of service in early design stages and shows students and professionals how to model reusable, parametrized components and configured, deployed systems in order to analyze service attributes.
Abstract: Too often, software designers lack an understanding of the effect of design decisions on such quality attributes as performance and reliability. This necessitates costly trial-and-error testing cycles, delaying or complicating rollout. This book presents a new, quantitative architecture simulation approach to software design, which allows software engineers to model quality of service in early design stages. It presents the first simulator for software architectures, Palladio, and shows students and professionals how to model reusable, parametrized components and configured, deployed systems in order to analyze service attributes. The text details the key concepts of Palladio's domain-specific modeling language for software architecture quality and presents the corresponding development stage. It describes how quality information can be used to calibrate architecture models from which detailed simulation models are automatically derived for quality predictions. Readers will learn how to approach systematically questions about scalability, hardware resources, and efficiency. The text features a running example to illustrate tasks and methods as well as three case studies from industry. Each chapter ends with exercises, suggestions for further reading, and "takeaways" that summarize the key points of the chapter. The simulator can be downloaded from a companion website, which offers additional material. The book can be used in graduate courses on software architecture, quality engineering, or performance engineering. It will also be an essential resource for software architects and software engineers and for practitioners who want to apply Palladio in industrial settings.

133 citations

BookDOI
TL;DR: This paper analyzes the applicability of various performance pre- diction methods for the development of component-based systems and contrast their inherent strengths and weaknesses in different engineering problem scenar- ios to establish a basis to select an appropriate prediction method.
Abstract: Performance predictions of component assemblies and the ability of obtaining system-level performance properties from these predictions are a cru- cial success factor when building trustworthy component-based systems. In order to achieve this goal, a collection of methods and tools to capture and analyze the performance of software systems has been developed. These methods and tools aim at helping software engineers by providing them with the capability to understand design trade-offs, optimize their design by identifying performance inhibitors, or predict a systems performance within a specified deployment envi- ronment. In this paper, we analyze the applicability of various performance pre- diction methods for the development of component-based systems and contrast their inherent strengths and weaknesses in different engineering problem scenar- ios. In so doing, we establish a basis to select an appropriate prediction method and to provide recommendations for future research activities, which could sig- nificantly improve the performance prediction of component-based systems.

110 citations


Cited by
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Posted Content
TL;DR: In this paper, the authors provide a unified and comprehensive theory of structural time series models, including a detailed treatment of the Kalman filter for modeling economic and social time series, and address the special problems which the treatment of such series poses.
Abstract: In this book, Andrew Harvey sets out to provide a unified and comprehensive theory of structural time series models. Unlike the traditional ARIMA models, structural time series models consist explicitly of unobserved components, such as trends and seasonals, which have a direct interpretation. As a result the model selection methodology associated with structural models is much closer to econometric methodology. The link with econometrics is made even closer by the natural way in which the models can be extended to include explanatory variables and to cope with multivariate time series. From the technical point of view, state space models and the Kalman filter play a key role in the statistical treatment of structural time series models. The book includes a detailed treatment of the Kalman filter. This technique was originally developed in control engineering, but is becoming increasingly important in fields such as economics and operations research. This book is concerned primarily with modelling economic and social time series, and with addressing the special problems which the treatment of such series poses. The properties of the models and the methodological techniques used to select them are illustrated with various applications. These range from the modellling of trends and cycles in US macroeconomic time series to to an evaluation of the effects of seat belt legislation in the UK.

4,252 citations

Journal ArticleDOI
TL;DR: The Palladio component model (PCM) is used to specify component-based software architectures in a parametric way to enable the prediction of extra-functional properties, and the resulting prediction accuracy is sufficient to support the evaluation of architectural design decisions.

749 citations

Journal ArticleDOI
TL;DR: Will Tracz, the esteemed editor and Used-Program salesman, has written an entertaining, non-technical book dealing with the practice (and lack of) of software reuse.
Abstract: Will Tracz, our esteemed editor and Used-Program salesman, has written an entertaining, non-technical book dealing with the practice (and lack of) of software reuse. Its a collection of essays, mostly rehashed (reused?) and updated from various columns and papers published over the years.. Its a short (a bit over 200 pages) easy reading and enjoyable book (I read most of it in one sitting). Some of the essays discuss what was printed in the past and a discussion of the current status of the points.

706 citations