System Software Reliability

Pham, Hoang

doi:10.1007/1-84628-295-0

Cited by 449 publications

(395 citation statements)

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“…We base our model in the well-known consecutive-k-out-of-n:F [49] theory, which accounts for the reliability of a system composed of an ordered sequence of n components, such that the system fails if, and only if, at least k consecutive components fail. In our case, the components are the packets of a flow, and the flow is split if at least k consecutive packets are not sampled, where…”

Section: Flow Splittingmentioning

confidence: 99%

Analysis of the impact of sampling on NetFlow traffic classification

et al. 2011

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The traffic classification problem has recently attracted the interest of both network operators and researchers. Several machine learning (ML) methods have been proposed in the literature as a promising solution to this problem. Surprisingly, very few works have studied the traffic classification problem with Sampled NetFlow data. However, Sampled NetFlow is a widely extended monitoring solution among network operators. In this paper we aim to fulfill this gap. First, we analyze the performance of current ML methods with NetFlow by adapting a popular ML-based technique. The results show that, although the adapted method is able to obtain similar accuracy than previous packet-based methods (≈90%), its accuracy degrades drastically in the presence of sampling. In order to reduce this impact, we propose a solution to network operators that is able to operate with Sampled NetFlow data and achieve good accuracy in the presence of sampling.

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Section: Flow Splittingmentioning

confidence: 99%

Analysis of the impact of sampling on NetFlow traffic classification

et al. 2011

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“…In this section, the SPRT methodology is applied on five different data sets that are borrowed from pham [16], lyu [17] and sonata [18] Table 1 for Burr Type III and Table 2 for Pareto Type II. Using the specification of b 0 , b 1 , and c 0 , c 1 from Table 1 and Table 2 the mean value functions m 0 (t) and m 1 (t) are computed for each 't' of the models.…”

Section: Sprt Analysis Of Live Data Setsmentioning

confidence: 99%

An Analogy of Burr Type III and Pareto Type II using SPRT

2017

IJIET

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Abstract-Software reliability is viewed as one of the key attributes of software quality, an important quality metric for any developed software. The aim is to statistically measure, ensure and predict the reliability of the software product and is accessed by the use of any statistical model, whose unknown parameters are estimated from the available software failure data. Researchers developed Sequential Probability Ratio Test (SPRT) to judge upon reliable/unreliable software based software reliability techniques. An analogy between Burr Type III and Pareto Type II with SPRT mechanism based on time domain data of Non Homogenous Poisson Process (NHPP) is presented here.

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“…Therefore, the modelling of software reliability and accurately predicting trends is essential for determining overall reliability of software. Numerous software reliability growth models (srgms) were developed during the last four decades [11,17,7,13] and still new models are being explored. One of the most important parameters which controls the growth of software reliability is the fault reduction factor (frf) proposed by Musa [9].…”

Section: C184mentioning

confidence: 99%

“…This phenomenon is called imperfect debugging. Previous studies [13,16,18,2] incorporated the concept of imperfect debugging. Recently, Ahmad et al [1] analysed a srgm by considering the log-logistic testing effort and imperfect debugging.…”

Section: C184mentioning

confidence: 99%

Cost optimization of a software reliability growth model with imperfect debugging and a fault reduction factor

Manjula

Jain²,

Gulati³

2014

ANZIAMJ

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In modern society people depend on both hardware and software systems. A software system is embedded in every activity of a computer system. The desired performance of a software system is an important issue for many critical systems. Over the past decades, many software models were proposed for estimating the growth of reliability. To improve software quality, software reliability growth models (srgm) play an important role. The present investigation deals with a srgm with imperfect debugging, change points and a fault reduction factor (frf). A frf is the net number of faults removed in proportion to the failures experienced. This article proposes a new scheme for constructing a srgm based on a non-homogeneous Poisson process by

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System Software Reliability

Abstract: British Library Cataloguing in Publication Data Pham, Hoang System software reliability. -(Springer series in reliability engineering) 1.Systems software 2.Computer software -Reliability I.Title 005.4'3 ISBN-10: 1852339500

Cited by 449 publications

References 0 publications

Analysis of the impact of sampling on NetFlow traffic classification

Analysis of the impact of sampling on NetFlow traffic classification

An Analogy of Burr Type III and Pareto Type II using SPRT

Cost optimization of a software reliability growth model with imperfect debugging and a fault reduction factor

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