Optimizing decomposition of software architecture for local recovery

Cataloged from PDF version of article.The increasing size and complexity of software systems has led to an amplified number of potential failures and as such makes it harder to ensure software reliability. Since it is usually hard to prevent all the failures, fault tolerance techniques have become more important. An essential element of fault tolerance is the recovery from failures. Local recovery is an effective approach whereby only the erroneous parts of the system are recovered while the other parts remain available. For achieving local recovery, the architecture needs to be decomposed into separate units that can be recovered in isolation. Usually, there are many different alternative ways to decompose the system into recoverable units. It appears that each of these decomposition alternatives performs differently with respect to availability and performance metrics. We propose a systematic approach dedicated to optimizing the decomposition of software architecture for local recovery. The approach provides systematic guidelines to depict the design space of the possible decomposition alternatives, to reduce the design space with respect to domain and stakeholder constraints and to balance the feasible alternatives with respect to availability and performance. The approach is supported by an integrated set of tools and illustrated for the open-source MPlayer software

PEVK Domain of Titin: An Entropic Spring with Actin-Binding Properties

A key issue in the MDA approach is the transformation of platform independent models to platform specific models. Before transforming to a platform specific model, however, it is necessary to select the appropriate platform. Various platforms exist with different properties and the selection of the appropriate platform for the given application requirements is not trivial. An inappropriate selection of a platform, though, may easily lead to unnecessary loss of resources and lower the efficiency of the application development. Unfortunately, the selection of platforms in MDA is currently implicit and lacks systematic support. We propose to integrate so-called platform selection rules in the MDA approach for systematic selection of platforms. The platform selection rules are based on platform domain models that are derived through domain analysis techniques. We show that the selection of platforms is important throughout the whole MDA process and discuss the integration of the platform selection rules in the MDA approach. The platform selection rules have been implemented in the prototypical tool MDA Selector that provides automated support for the selection of a platform. The presented ideas are illustrated for a stock trading system