Software Diversity—Some Considerations About its Benefits and its Limitations

Saglietti, Francesca; Ehrenberger, W.

doi:10.1016/b978-0-08-034801-8.50011-8

Cited by 22 publications

(4 citation statements)

References 3 publications

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“…Various arguments have been used to determine the test duration in discrete time, that is, to determine a lower bound on the number N of test inputs required to ensure that P, the actual failure probability per execution, is less than or equal to a value Po with a given confidence level. In [18,27,38) the authors make use of relations similar to equation (1), and in [9,14) the classical theory of hypothesis testing is called upon. All of these studies, however, lead to relation (2) in which QN corresponds to the confidence level [39).…”

Section: Reliability Evaluation From a Zero-failure Test Experimentsmentioning

confidence: 99%

“…Assuming that the failure process is governed by a constant hazard rate (the failure occurrences conform to a Poisson distribution), the evaluation in continuous time yields a similar formula. The testing time T required to ensure that the software meets a failure rate Ao with a confidence level (I-Eo), see for example [13,18], is:…”

Section: Reliability Evaluation From a Zero-failure Test Experimentsmentioning

confidence: 99%

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An investigation of statistical software testing

Thévenod-Fosse

Waeselynck

1991

Software Testing Verif & Rel

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Software validation embodies two notions: fault removal and fault forecasting. Statistical testing involves exercising a piece of software by supplying it with input values that are randomly selected according to a defined probability distribution on its input domain. It can be used as a practical tool for revealing faults in a fault removal phase, and for assessing software dependability in a fault forecasting phase. In both of these, its efficiency is linked to the adequacy of the input probability distribution with respect to the test experiment goal. In this paper a mixed validation strategy combining deterministic and random test data is defined, and the theoretical and experimental work performed to support the strategy is reported. The quoted results relate to the unit testing of four real programs from the nuclear field. They confirm the high fault revealing power of statistical structural testing. Two main directions for further investigation of statistical testing are indicated by the reported work. These are described and solutions to the associated problems are outlined.

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Section: Reliability Evaluation From a Zero-failure Test Experimentsmentioning

confidence: 99%

Section: Reliability Evaluation From a Zero-failure Test Experimentsmentioning

confidence: 99%

An investigation of statistical software testing

Thévenod-Fosse

Waeselynck

1991

Software Testing Verif & Rel

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“…Correlated errors form a main source of failure of the N-version programs. Correlated errors can be minimized by design diversity [14,15,302]. A design paradigm has been developed to assure design diversity in N-version software [221].…”

Section: N-version Programmingmentioning

confidence: 99%

Software reliability models for critical applications

Pham¹,

Pham²

1991

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This report presents the results of the first phase of the ongoing EG&G Idaho, Inc., Software Reliability Research Program. The program is studying the existing software reliability mc:lels and proposes a state-of-the-art software reliability model that is relevant to the nuclear reactor control environment. This report consists of three parts: (1) summaries of the literature review of existing software reliability and fault tolerant software reliability models and their related issues, (2) proposed technique for saitware reliability enhancement, and (3) general discussion and future research.

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“…Solche gemeinsamen Fehlreaktionen sollten zumindest wesentlich seltener sein als die Fehlreaktion eines Programmes allein. (Für Abnahmetests kann man sich mit einer schwächeren Forderung begnügen, so daß die folgende Kritik diesen Fall nicht betrifft [7].) Aufgrund von Korrelationsbestimmungen sind Zweifel an der Basisannahme laut geworden.…”

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Diversitäre Programmierung: Kein Allheilmittel

Grams¹

1986

it - Information Technology

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Software Diversity—Some Considerations About its Benefits and its Limitations

Cited by 22 publications

References 3 publications

An investigation of statistical software testing

An investigation of statistical software testing

Software reliability models for critical applications

Diversitäre Programmierung: Kein Allheilmittel

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