19.09.2011: Article accepted for publication in TSE Journal

A new article covering reliability prediction was accepted for publication in the IEEE Transactions on Software Engineering.

The journal article "Architecture-based reliability prediction with the Palladio Component Model" covering reliability prediction based on the Palladio Component Model has been accepted for publication in the IEEE Transactions on Software Engineering (TSE). The TSE is a top-10-ranked journal in computer science / software engineering, and it is the second most cited IEEE Computer Society journal, with an impact factor of 3.75 (2009).

Kontakt:

Franz Brosch
Wiss. Mirarbeiter im Forschungsbereich Software Engineering (SE)
E-Mail: This e-mail address is being protected from spambots. You need JavaScript enabled to view it
Tel.: 0721-9654-614

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Abstract:

With the increasing importance of reliability in business and industrial software systems, new techniques of architecture-based reliability engineering are becoming an integral part of the development process. These techniques can assist system architects in evaluating the reliability impact of their design decisions. Architecture-based reliability engineering is only effective if the involved reliability models reflect the interaction and usage of software components and their deployment to potentially unreliable hardware. However, existing approaches either neglect individual impact factors on reliability or hard-code them into formal models, which limits their applicability in component-based development processes. This paper introduces a reliability modelling and prediction technique that considers the relevant architectural factors of software systems by explicitly modelling the system usage profile and execution environment and automatically deriving component usage profiles. The technique offers a UML-like modelling notation, whose models are automatically transformed into a formal analytical model. Our work builds upon the Palladio Component Model, employing novel techniques of information propagation and reliability assessment. We validate our technique with sensitivity analyses and simulation in two case studies. The case studies demonstrate effective support of usage profile analysis and architectural configuration ranking, together with the employment of reliability-improving architecture tactics.