This paper addresses the issue of characterizing the respective impact of fault injection techniques. Three physical techniques and one software-implemented technique that have been used to assess the fault tolerance features of the MARS fault-tolerant distributed real-time system are compared and analyzed. After a short summary of the fault tolerance features of the MARS architecture and especially of the error detection mechanisms that were used to compare the erroneous behaviors induced by the fault injection techniques considered, we describe the common distributed testbed and test scenario implemented to perform a coherent set of fault injection campaigns. The main features of the four fault injection techniques considered are then briefly described and the results obtained are finally presented and discussed. Emphasis is put on the analysis of the specific impact and merit of each injection technique.

/pdf/comparison-of-physical-and-software-implemented-fault-4fxzbenped.pdf

Comparison of physical and software-implemented fault injection techniques

Postgraduate Students: Vladimír Arnot, Daniel Čapek, Rudolf Čejka, Dao Minh, Tomá Dulík, Martin Hrubý, Radek Kočí, Petr Kotásek, Marek Křejpský, Bohuslav Křena, Vladislav Kubíček, Vladimír Marek, Petr Matouek, Ale Mičín, Jiří Očenáek, Tomá Ondráček, Petr Peňás, Jaroslav Ráb, Richard Růička, Luká Sekanina, Ivan Schwarz, Azedien Sllame, Petr Smolík, Jiří Staroba, Josef Strnadel, Luká Szemla, Pavel Tinovský, Michal Tomů, Milan Urbáek, Michal Vojkůvka, Petr Vurm, Frantiek Zbořil

Department of Computer Science and Engineering

This paper presents a benchmark for dependable systems The benchmark consists of two metrics, number of catastrophic incidents and performance degradation, which are obtained by a tool that (1) generates synthetic workloads that produce a high level of CPU, memory, and I/O activity and (2) injects CPU, memory, and I/O faults according to an injection strategy The benchmark has been installed on two TMR-based prototype machines: TMR Prototype A and TMR Prototype B An implementation for a third prototype, is based on a duplex architecture, is in progress The results demonstrate the utility of the benchmark in comparing the system-level fault tolerance of these machines and in providing insight into their design In particular the benchmark shows that Prototype B suffers fewer catastrophic incidents than Prototype A under the same workload conditions and fault injection method However Prototype B also suffers more performance degradation in the presence of faults, which might be an important concern for time-critical applications

An approach towards benchmarking of fault-tolerant commercial systems

Context: With the increased use of software for running key functions in modern society it is of utmost importance to understand software robustness and how to support it. Although there have been many contributions to the field there is a lack of a coherent and summary view. Objective: To address this issue, we have conducted a literature review in the field of robustness. Method: This review has been conducted by following guidelines for systematic literature reviews. Systematic reviews are used to find and classify all existing and available literature in a certain field. Results: From 9193 initial papers found in three well-known research databases, the 144 relevant papers were extracted through a multi-step filtering process with independent validation in each step. These papers were then further analyzed and categorized based on their development phase, domain, research, contribution and evaluation type. The results indicate that most existing results on software robustness focus on verification and validation of Commercial of the shelf (COTS) or operating systems or propose design solutions for robustness while there is a lack of results on how to elicit and specify robustness requirements. The research is typically solution proposals with little to no evaluation and when there is some evaluation it is primarily done with small, toy/academic example systems. Conclusion: We conclude that there is a need for more software robustness research on real-world, industrial systems and on software development phases other than testing and design, in particular on requirements engineering.

http://robertfeldt.net/publications/shahrokni_2013_sysrev_robustness.pdf

A systematic review of software robustness

As computer systems become more complex and mission-critical, it becomes imperative for systems engineers and researchers to have metrics for a system's "illities": dependability, reliability, availability, and serviceability. Written by leading experts, Dependability Benchmarking for Computer Systems provides a comprehensive collection of benchmarks for measuring dependability in hardware-software systems, and explains the concepts behind them. It collects the expert knowledge from DBench, a special research project funded by the European Union, to provide an inclusive text for engineers, researchers, system vendors, system purchasers, dependability researchers, computer industry consultants, and system integrators.

/pdf/dependability-benchmarking-for-computer-systems-1nuw2rxzzz.pdf

Dependability Benchmarking for Computer Systems

Inability to identify weaknesses or to quantify advancements in software system robustness frequently hinders the development of robust software systems. Efforts have been made to develop benchmarks of software robustness to address this problem, but they all suffer from significant shortcomings. The paper presents the various features that are desirable in a benchmark of system robustness, and evaluates some existing benchmarks according to these features. A new hierarchically structured approach to building robustness benchmarks, which overcomes many deficiencies of past efforts, is also presented. This approach has been applied to building a hierarchically structured benchmark that tests part of the Unix file and virtual memory systems. The resultant benchmark has successfully been used to identify new response class structures that were not detected in a similar situation by other less organized techniques.

Measuring software dependability by robustness benchmarking

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Measuring software dependability by robustness benchmarking