Embedded and mobile software systems are marked with a high degree of unpredictability and dynamism in the execution context. At the same time, such systems are often mission-critical, meaning that they need to satisfy strict reliability requirements. Most current software reliability analysis approaches are not suitable for these types of software systems, as they do not take the changes in the execution context of the system into account. We propose an approach geared to such systems which continuously furnishes refined reliability predictions at runtime by incorporating various sources of information, including the execution context of the system. The reliability predictions are leveraged to proactively place the software in the (near-)optimal configuration with respect to changing conditions. Our approach considers two representative architectural reconfiguration decisions that impact the system's reliability: reallocation of components to processes and changing the number of component replicas. We have realized the approach as part of a framework intended for mission-critical settings, called REsilient SItuated SofTware system (RESIST), and evaluated it using a mobile emergency response system.

Situated software systems are an emerging class of systems that are predominantly pervasive, embedded, and mobile. They are marked with a high degree of unpredictability and dynamism in the execution context. At the same time, such systems often need to satisfy strict reliability requirements. Most current software reliability analysis approaches are not suitable for situated software systems. We propose an approach geared to such systems, which continuously furnishes refined reliability predictions at runtime by incorporating various sources of information. The reliability predictions are leveraged to proactively place the software in the optimal configuration with respect to changing conditions. Our approach considers two representative architectural reconfiguration decisions that impact the system's reliability: reallocation of components to processes and changing the architectural style. We have realized the approach as part of a framework intended for mission-critical settings, called REsilient SItuated SofTware system (RESIST), and evaluated it using a mobile emergency response system.

Mobile software systems are characterized by their highly dynamic and unpredictable execution context. Such systems are permeating a number of domains where the systems operate in constantly changing conditions. We refer to such systems as Situated Software Systems. These systems are often deployed in mission-critical settings with stringent reliability requirements. Existing approaches to performing reliability analysis are insufficient in meeting the demands of situated software systems. We propose an approach aimed at such systems and present it in the form of a framework and tool suite known as REsilient SItuated SofTware system (RESIST). The framework utilizes information from the system's context to produce reliability predictions, and places the system in the optimally reliable configuration with respect to other competing quality attributes.