No abstract

Modern society relies heavily on complex software systems for everyday activities. Dependability of these systems thus has become a critical feature that determines which products are going to be successfully and widely adopted. In this paper, we present an approach to modeling reliability of software systems at the architectural level. Dynamic Bayesian Networks are used to build a stochastic reliability model that relies on standard models of software architecture, and does not require implementation-level artifacts. Reliability values obtained via this approach can aid the architect in evaluating design alternatives. The approach is evaluated using sensitivity and uncertainty analysis.

As with any other artifact produced as part of the software life cycle, software architectures evolve and this evolution must be managed. One approach to doing so would be to apply any of a host of existing configuration management systems, which have long been used successfully at the level of source code. Unfortunately, such an approach leads to many problems that prevent effective management of architectural evolution. To overcome these problems, we have developed an alternative approach centered on the use of an integrated architectural and configuration management system model. Because the system model combines architectural and configuration management concepts in a single representation, it has the distinct benefit that all architectural changes can be precisely captured and clearly related to each other-both at the fine-grained level of individual architectural elements and at the coarse-grained level of architectural configurations. To support the use of the system model, we have developed Mae, an architectural evolution environment through which users can specify architectures in a traditional manner, manage the evolution of the architectures • 241 using a check-out/check-in mechanism that tracks all changes, select a specific architectural configuration, and analyze the consistency of a selected configuration. We demonstrate the benefits of our approach by showing how the system model and its accompanying environment were used in the context of several representative projects.

In the world of software development everything evolves. So, then, do software architectures. Unlike source code, for which the use of a configuration management (CM) system is the predominant approach to capturing and managing evolution, approaches to capturing and managing architectural evolution span a wide range of disconnected alternatives. This paper contributes a novel architecture evolution environment, called Mae, which brings together a number of these alternatives. The environment facilitates an incremental design process in which all changes to all architectural elements are integrally captured and related. Key to the environment is a rich system model that combines architectural concepts with those from the field of CM. Not only does this system model form the basis for Mae, but in precisely capturing architectural evolution it also facilitates automated support for several innovative capabilities that rely on the integrated nature of the system model. This paper introduces three of those: the provision of design guidance at the architectural level, the use of specialized software connectors to ensure run-time reliability during component upgrades, and the creation of component-level patches to be applied to deployed system configurations.

Over the past decade a number of architecture description languages (ADLs)