10th IEEE High Assurance Systems Engineering Symposium (HASE'07) 2007
DOI: 10.1109/hase.2007.39
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Improving Reliability and Safety by Trading off Software Failure Criticalities

Abstract: A number of voters have been proposed for n-version programming diversity designed software systems. The knowledge about various software failure criticalities is not incorporated in the decisions of these voters. Moreover, failure classes contradict among each other with respect to their fault tolerance requirements, as a result, current voters either consider different failures equally or they mask only certain types of failures. Therefore, the voters need to consider system criticalities to different failur… Show more

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Cited by 12 publications
(4 citation statements)
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References 34 publications
(18 reference statements)
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“…Most of these efforts focus on increasing system reliability during the software design by enhancing the composition among system components [1,24,39,41,49,51,58].…”
Section: Reliable Design and Operational Activities Of Software Archimentioning
confidence: 99%
“…Most of these efforts focus on increasing system reliability during the software design by enhancing the composition among system components [1,24,39,41,49,51,58].…”
Section: Reliable Design and Operational Activities Of Software Archimentioning
confidence: 99%
“…In order to increase the automation level of vulnerability mining, fuzzing was introduced by Mendonça and Neves [12] to test Wi-Fi, which was early used in finding defects of wire network protocols. Lahmadi et al [21] also applied fuzzing on discovering vulnerabilities in 6LoWPAN networks and designed a testing framework.…”
Section: Related Workmentioning
confidence: 99%
“…Some researchers proposed testing cases generation algorithms in different ways for improving the efficiency of fuzzing test. The general refined fuzzing algorithms are structure-based algorithm [10], key-field-based algorithm [11], and boundary-based algorithm [12]. However, the relationship between testing cases and the transformation of operation state of the target system are not taken into account in the refined algorithms.…”
Section: Introductionmentioning
confidence: 99%
“…The commonly used algorithms for voting differ in the requirements management of the original data and voting schemes. 1924 Some of the algorithms depending on the version given by the data set may be ineffective. The voting algorithms are mainly classified into two categories: voting algorithms established by the output data comparison and voting algorithms where the decision making does not rely on the likeness of the output.…”
Section: Introductionmentioning
confidence: 99%