Data criticality estimation in software applications

In safety-critical applications it is often possible to exploit software techniques to increase system's fault- tolerance. Common approaches are based on data redundancy to prevent data corruption during the software execution. Duplicating most critical variables only can significantly reduce the memory and performance overheads, while still guaranteeing very good results in terms of fault-tolerance improvement. This paper presents a new methodology to compute the criticality of variables in target software applications. Instead of resorting to time consuming fault injection experiments, the proposed solution is based on the run- time analysis of the variables' behavior logged during the execution of the target application under different workloads

A Dependable Autonomic Computing Environment for Self-Testing of Complex Heterogeneous Systems

AbstractThis paper is part of a R&D project aiming at the definition and implementation of an environment for dependable autonomic computing. The primary goal of the study is the increase of dependability of digital systems using self-healing techniques. Mobile agents implement self-testing policies for complex and heterogeneous systems. The aim of this paper is to present the general ideas of the project, describe the design decisions and a detailed view of the current architecture. The research includes design and development of a working prototype