1,721,084 research outputs found
Enabling On-Line Dependability Assessment of Android Smart Phones
No full textThe increasing complexity of smart phones introduces new dependability threats. Often, novel applications and features are delivered with scarce testing, due to the impressive market pressure. Despite these concerns, there is still little understanding on the dependability behavior of today smart phones. This paper proposes the design of a logging platform for the Android OS. The logging platform enables the collection of failure data, useful to assess the dependability of smart phones at runtime. Preliminary experimental results on real-world Android devices show the feasibility of the approach and encourage further research activities
International Journal on Adaptive, Resilient, and Autonomic Systems (IJARAS), Special Issue on Adaptive and Dependable Mobile Ubiquitous Systems
No full textModeling and Analyzing the Dependability of Short-Range Wireless Technologies via Field Failure Data Analysis
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An empirical analysis of error propagation in critical software systems
No full textError propagation analysis is a consolidated practice to gain insights into error modes and effects that pertain to the activation of faults in software systems. A variety of approaches, such as architecture-based, source code instrumentation and variable tracing, have been proposed so far to address software error propagation analysis. Although valuable, existing approaches entail a substantial degree of system internals’ knowledge, visibility and code manipulation that is not well-suited for real-life production environments. This paper proposes an empirical analysis of error propagation. We specifically address the challenges in using fault data and error events in the logs, which are a convenient byproduct of the system’s execution. The approach puts forth the construction of error reporting graphs. We apply the approach to 2,042 failure data points from two real-world critical systems from the Air Traffic Control domain by a top industry provider. The approach contributes to develop a deep understanding on error modes and propagation paths, which can be leveraged by practitioners to make informed decisions on the placement of error detection mechanisms
Dependable Services for Mobile Health Monitoring Systems
No full textThe design and realization of health monitoring systems has attracted the interest of large communities both from industry and academia. Remote and continuous monitoring of patient’s vital signs is the target of an emerging business market that aims both to improve the quality of life of patients and to reduce costs of national healthcare services. Such applications, however, are particularly critical from the point of view of dependability. This presents the design of a set of services for the assurance of high degrees of dependability to generic mobile health monitoring systems. The design is based on the results of a detailed failure modes and effects analysis (FMEA), conducted to identify the typical dependability threats of health monitoring systems. The FMEA allowed the authors to conceive a set of configurable monitoring services, enriching the system with the ability to detect failures at runtime, and enabling the realization of dependable services for future mobile health monitoring systems
Event Logs for the Analysis of Software Failures: A Rule-Based Approach
No full textEvent logs have been widely used over the last three decades to analyze the failure behavior of a variety of systems. Nevertheless, the implementation of the logging mechanism lacks a systematic approach and collected logs are often inaccurate at reporting software failures: This is a threat to the validity of log-based failure analysis. This paper analyzes the limitations of current logging mechanisms and proposes a rule-based approach to make logs effective to analyze software failures. The approach leverages artifacts produced at system design time and puts forth a set of rules to formalize the placement of the logging instructions within the source code. The validity of the approach, with respect to traditional logging mechanisms, is shown by means of around 12,500 software fault injection experiments into real-world systems
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