Rare conditions-an important cause of failures

Hecht, H.

doi:10.1109/cmpass.1993.288855

Cited by 27 publications

(11 citation statements)

References 6 publications

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“…It appears from the anomalies we studied that one consequence of a complex system highly coupled with its environment is that some anomalies have multiple triggers with the same degree of importance and with similar temporal proximities to the anomaly. This finding is consistent with previous experience of similar systems [15], [21] and with comments on ODC by a 1996 panel on statistical software engineering. They described the nonuniqueness as "multiple spawning," in which "although the defect types are mutually exclusive, it is possible that a fault may result in many defects and vice versa" [9].…”

Section: Triggersupporting

confidence: 82%

“…The basis for this query was a 1993 finding by Hecht that "Rare events were clearly the leading cause of failures among the most severe failure categories" [15]. Examination of the data (Fig.…”

Section: Triggermentioning

confidence: 99%

“…The safety-critical anomalies per spacecraft numbered 8,8,15,19,29,59, and 61, for a total of 199. The only data points that were removed from the original data set were four duplicates.…”

Section: Approachmentioning

confidence: 99%

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Empirical analysis of safety-critical anomalies during operations

Lutz

Mikulski

2004

IIEEE Trans. Software Eng.

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Abstract-Analysis of anomalies that occur during operations is an important means of improving the quality of current and future software. Although the benefits of anomaly analysis of operational software are widely recognized, there has been relatively little research on anomaly analysis of safety-critical systems. In particular, patterns of software anomaly data for operational, safety-critical systems are not well understood. This paper presents the results of a pilot study using Orthogonal Defect Classification (ODC) to analyze nearly two hundred such anomalies on seven spacecraft systems. These data show several unexpected classification patterns such as the causal role of difficulties accessing or delivering data, of hardware degradation, and of rare events. The anomalies often revealed latent software requirements that were essential for robust, correct operation of the system. The anomalies also caused changes to documentation and to operational procedures to prevent the same anomalous situations from recurring. Feedback from operational anomaly reports helped measure the accuracy of assumptions about operational profiles, identified unexpected dependencies among embedded software and their systems and environment, and indicated needed improvements to the software, the development process, and the operational procedures. The results indicate that, for long-lived, critical systems, analysis of the most severe anomalies can be a useful mechanism both for maintaining safer, deployed systems and for building safer, similar systems in the future.

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Section: Triggersupporting

confidence: 82%

Section: Triggermentioning

confidence: 99%

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Empirical analysis of safety-critical anomalies during operations

Lutz

Mikulski

2004

IIEEE Trans. Software Eng.

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“…Second, a vulnerability, whose exploitation is highly unlikely in a given application scenario but whose exploitation consequences are of disastrous impact, would be ignored by operational profiles. However, critical system failures often result from highly unlikely and hence unexpected conditions that are by definition not covered by operational profiles [10,31,21].…”

Section: Introductionmentioning

confidence: 99%

The impact of fault models on software robustness evaluations

Winter

Sârbu

Suri

et al. 2011

Proceedings of the 33rd International Conference on Software Engineering

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Following the design and in-lab testing of software, the evaluation of its resilience to actual operational perturbations in the field is a key validation need. Software-implemented fault injection (SWIFI) is a widely used approach for evaluating the robustness of software components. Recent research [24,18] indicates that the selection of the applied fault model has considerable influence on the results of SWIFI-based evaluations, thereby raising the question how to select appropriate fault models (i.e. that provide justified robustness evidence).This paper proposes several metrics for comparatively evaluating fault models's abilities to reveal robustness vulnerabilities. It demonstrates their application in the context of OS device drivers by investigating the influence (and relative utility) of four commonly used fault models, i.e. bit flips (in function parameters and in binaries), data type dependent parameter corruptions, and parameter fuzzing. We assess the efficiency of these models at detecting robustness vulnerabilities during the SWIFI evaluation of a real embedded operating system kernel and discuss application guidelines for our metrics alongside.

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“…unlikely) events. A number of studies, such as [HEC93] and [HEC94] have shown that many failures in well-tested systems are caused by such events. The same data from these studies also shows that multiple rare events are almost the exclusive cause of the most c;ritical failures in these systems.…”

Section: "Approximately 15/x Hours Of Test Time Under the Most Optimmentioning

confidence: 99%

Assessing multi-version systems through fault injection

Townend

Proceedings of the Seventh IEEE International Workshop on Object-Oriented Real-Time Dependable Systems. (WORDS 2002)

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The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source• a link is made to the metadata record in Durham E-Theses• the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders. This approach has the potential for yielding highly useful metrics with regard to MVD systems, as well as giving developers a greater insight into the behaviour of each channel ' within the system. In this research, an automatic fault injection system for multi-version systems called FITMVS is developed. A multi-version system is then,tested using this system, and the results analysed.It is concluded that this appr?ach can yield several extremely useful metrics, such as metrics related to channel sensitivity, channel sensitivity to common-mode error, program scope sensitivity, program scope sensitivity to common-mode error, error frequency distribution and common-mode error frequency distribution. In addition to this, the analysis of the multiversion system tested indicates that the system has an extremely low probability of experiencing common-mode error, although several key points in ch~nnel code are identified as having higher sensitivity to faults than others.2

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Rare conditions-an important cause of failures

Cited by 27 publications

References 6 publications

Empirical analysis of safety-critical anomalies during operations

Empirical analysis of safety-critical anomalies during operations

The impact of fault models on software robustness evaluations

Assessing multi-version systems through fault injection

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