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Fault injection has been an important mechanism to test the dependability properties of a system. Through this mechanism, it is possible to analyze the behavior of a computer program in case of anomalies and to obtain useful statistics to measure the effectiveness of techniques for fault tolerance. In areas such as telecommunications, aviation and finance, the use of fault tolerance is a common practice, although, in the development of simple embedded systems it usually does not occur. Due to this reason, there is a need to create tools for noninvasive tests that allow simulating faults without dramatically increasing the system complexity. This article presents some of the techniques often used to impose fault tolerance and describes a system developed for fault injection, which operates by inserting faults in certain memory regions to change the data and to cause crashes in a rapid prototyping platform for microcontrollers. At the end of this article the results are presented.

Literatures in the health areas are reported frequently on accidents caused by problems with shock during surgery in both patients as the clinical team. It should be noted that most electrical equipment, during use, is often in contact with the patient and / or with medical professionals. Therefore, the electric shock danger always exists in this environment. To avoid this, some equipment has been identified for monitoring IT-system and the use of these normally required by standards. The research described in this paper presents an electrical safety and information system in a critical environment on the hospital that meets the standard. This system has an insulation monitoring device and annunciator, part of the IT-system, with unpublished characteristics.

This paper describes the implementation of fault tolerance techniques (based on data and processing redundancy) in programming of a rapid prototyping platform using microcontrollers. To evaluate performance of these techniques was used a fault injector software and a weather station system as a case study. Experiments simulated faults in sensor readings and faults in SRAM memory regions of the weather station. Finally, the fault-tolerant system performance is presented in comparison with non-fault-tolerant system, considering incidence of failures, processing time, memory and power consumption.

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