RESIST: Resilient Situated Software Systems

RESIST is a framework intended to address reliability concerns in mission critical, dynamic and mobile settings.


Systems that are predominantly pervasive, embedded, and mobile are marked with a high degree of unpredictability and dynamism in the execution context. RESIST continuously monitors the system at run-time and produces reliability predictions by using monitoring data, and by incorporating various sources of information including architectural models and contextual information. The reliability predictions are derived at component and system-level, which are then leveraged to proactively to place the system in a near-optimal configuration.

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RESIST Framework

Architecture-based reliability models along with contextual and monitoring information obtained from the system are used by the Component-Level Reliability Analyzer to predict the reliability of system's components in their near future operation. These fine-grained reliability estimates are utilized by the Configuration Reliability Analyzer to determine the reliability of alternative configurations for the system. The Configuration Selector is in turn used to select a suitable configuration for the near future operation of the system. The Configuration Selector may use other quality attributes, such as performance, in making the configuration selection.

Once a new configuration is selected, the Context-Aware Middleware adapts the system at run-time to reflect the changes in configuration. The Context-Aware Middleware provides support for execution, monitoring, and adaptation of a software system in terms of its architectural constructs (e.g., components, connectors, and configuration).

Download and Setup Guidelines

Before setting up RESIST framework, the following tools and environments need to be setup as they are prerequisites:

Follow these steps to download the various components in the RESIST framework and to execute cases studies and examples.


More details about RESIST can be found in our publication:

Research Project Members

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