物件導向軟體之架構(Object-Oriented Software Construction)探討

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.

Forecasting, Structural Time Series Models and the Kalman Filter

[서평]「Component Software」 - Beyond Object-Oriented Programming -

The Palladio component model for model-driven performance prediction

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.

Safeware: System Safety and Computers

In cloud computing, software engineers design systems for virtually unlimited resources that cloud providers account on a pay-per-use basis. Elasticity management systems provision these resource autonomously to deal with changing workloads. Such workloads call for new objective metrics allowing engineers to quantify quality properties like scalability, elasticity, and efficiency. However, software engineers currently lack engineering methods that aid them in engineering their software regarding such properties. Therefore, the CloudScale project developed tools for such engineering tasks. These tools cover reverse engineering of architectural models from source code, editors for manual design/adaption of such models, as well as tools for the analysis of modeled and operating software regarding scalability, elasticity, and efficiency. All tools are interconnected via ScaleDL, a common architectural language, and the CloudScale Method that leads through the engineering process. In this tutorial, we execute our method step-by-step such that every tool and ScaleDL are briefly introduced.

https://dl.acm.org/doi/pdf/10.1145/2668930.2688818

The CloudScale Method for Software Scalability, Elasticity, and Efficiency Engineering: a Tutorial

https://sdqweb.ipd.kit.edu/publications/pdfs/kapova2010a.pdf

Systematic Refinement of Performance Models for Concurrent Component-based Systems

In this paper we outline an approach to the formalization of Web Service composition using WSBPEL (formerly BPEL4WS). Complementing current specification by adding protocol information, and making use of process algebra to model both Web Service and business process dynamic behaviour, we highlight key issues regarding the analysis of Web Service compatibility in the context of a business process managing their interaction.

New Issues on Coordination and Adaptation Techniques. Proceedings of the Second International Workshop on Coordination and Adaptation Techniques for Software Entities (WCAT'05).

Model-Driven Software Engineering (MDSE) is a widely used approach to deal with the increasing complexity of software. This increasing complexity also leads to the fact that the models used and the model transformations applied become larger and more complex as well. This means that the execution performance of model transformations is gaining in importance. While improving the performance of model transformation execution engines has been a focus of the MDSE-community in the past, there does not exist any empirical study on how developers of model transformation deal with performance issues. Consequently, we conducted an exploratory mixed method study consisting of a quantitative online survey and a qualitative interview study. We used a questionnaire to investigate whether the performance of a transformation is actually important for transformation developers and whether they have already tried to improve the performance of a model transformation. Subsequently, we conducted semi-structured interviews based on the answers to the questionnaire to investigate how transformation developers deal with performance issues, what causes and solutions they found and also what they think could help them to easier find causes. The results of the quantitative online survey show that 43 of 81 participants have already tried to improve the performance of a transformation and 34 of the 81 are sometimes or only rarely satisfied with the execution performance. Based on the answers from our 13 interviews, we identified different strategies to prevent or find performance issues in model transformations as well as different types of causes of performance issues and solutions. Finally, we compiled a collection of additional tool features perceived helpful by the interviewees to address performance issues.

An exploratory study on performance engineering in model transformations

Engineering high quality software is a tough task. In order to know whether a certain quality attribute has been achieved or degraded, it has to be quantified by analysis or measured. However, determining what to quantify and how these quantities are related to each other is the difficult part. Early analysis of the quality attributes of a software system on the basis of the system's planned architecture allows informed decisions on design trade-offs. Such decisions can be later validated by measurements on the running system.In this paper, we revisit software quality attributes. In particular, we introduce a generic taxonomy of quality attributes, the relationship between the attributes is argued, and finally we devise future work leading to an attribute-based methodology for evaluating software architectures. The goal is reasoning about multiple quality attributes of software systems to achieve the ability to quantitatively evaluate and trade-off them.

Steffen Becker

Papers

The CloudScale Method for Software Scalability, Elasticity, and Efficiency Engineering: a Tutorial

Systematic Refinement of Performance Models for Concurrent Component-based Systems

New Issues on Coordination and Adaptation Techniques. Proceedings of the Second International Workshop on Coordination and Adaptation Techniques for Software Entities (WCAT'05).

An exploratory study on performance engineering in model transformations

Towards a methodology driven by relationships of quality attributes for qos-based analysis