Selecting software reliability growth models and improving their predictive accuracy using historical projects data

Rana, Rakesh; Staron, Miroslaw; Berger, Christian; Hansson, Jörgen; Nilsson, Martin; Törner, Fredrik; Meding, Wilhelm; Höglund, Christoffer

doi:10.1016/j.jss.2014.08.033

Cited by 62 publications

(16 citation statements)

References 26 publications

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“…As Zhao and Xie (1996) state MLPE is the most common approach used while estimating the parameters of NHPP models, therefore in this research the MLPE is used and the function sets were solved with the use of MATLAB and MATLAB Optimization Toolbox. To assess which NHPP SRMs are performing best and when it is more appropriate for them to be applied during a project timeline, the approach proposed by Rana et al (2014) was employed in this study. The NHPP SRMs in question were evaluated by using full and partial data sets.…”

Section: Methodsmentioning

confidence: 99%

“…Software Reliability: is (a) the probability that software will not cause the failure of a system for a specified time under specified conditions, or (b) SRMs are used to estimate the total number of defects and the rate of software deterioration within a particular time period by using numeric data and are the result of applying reliability engineering theory to the software development domain (Rana, et al, 2014). The deterioration behavior of the software is predicted by using the known or assumed characteristics of the software in question (Lai & Garg, 2012).…”

Section: Introductionmentioning

confidence: 99%

“…During the initial testing processes, some of the software defects are identified and resolved; as the tests progress over time the number of unidentified defects continuously decrease, in other words as the probability of finding a defect decreases as the reliability of the software increases (Yamada, 2014). As stated by Rana et al (2014), the SRMs mainly try to answer two very practical question: "when the attained software quality is enough so that the testing can stop?" and "considering the remaining defects, is the software ready to be released?".…”

Section: Introductionmentioning

confidence: 99%

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2016

AJIT-e

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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2016

AJIT-e

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“…The considerable number of works, including the work of G. Myers [16] and to the latest researches [17][18][19][20][21][22][23][24][25][26] are devoted to the reliability of software.…”

Section: How To Assess the Reliability Of Training Programsmentioning

confidence: 99%

The probability estimation of the electronic lesson implementation taking into account software reliability

Gurov¹

2017

AIP Conference Proceedings

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“…With continuous debugging, analysis and correction, the software reliability will grow gradually with testing [33]. During the past three decades, numerous software reliability growth models (SRGMs) have been proposed [2,7,24,26,35,40,41].…”

Section: Introductionmentioning

confidence: 99%

Modeling of software fault detection and correction processes with fault dependency

Peng

Zhai

2017

EiN

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Modeling of software fault detection and correction processes with fault dependencyModelowanie procesów wykrywania i korekcji błędów oprograMowania z założenieM wzajeMnej zależności błędów Keywords: fault dependency, non-homogeneous Poisson process (NHPP), software reliability growth model (SRGM), software fault detection and correction processes. Modelowanie niezawodności oprogramowania w ciągu ostatnich trzech dekad ulegało ciągłej ewolucji, pozwalającej dostosować je do różnych, stale zmieniających się środowisk testowych. W przypadku istniejących modeli, dwoma podstawowymi i powszechnie stosowanymi założeniami jest natychmiastowe usunięcie błędu oraz brak zależności między błędami. Ostatnio, badacze zaproponowali modele, które łagodzą pierwsze z tych założeń, łącząc proces wykrywania błędów (FDP) z procesem ich korekcji (FCP). W niniejszym artykule, rozszerzono tę metodologię, proponując paradygmat modelowania dla zintegrowanych procesów FDP i FCP uwzględniający zależności między błędami. W paradygmacie tym, błędy klasyfikuje się jako błędy nadrzędne i błędy zależne, a procesy FCP dla obu typów błędów są modelowane oddzielnie. Zaproponowano kilka połączonych w pary modeli rozważających różne założenia dotyczące opóźnień debugowania w procesach łączących detekcję i korekcję błędów. Możliwość zastosowania proponowanych modeli przedstawiono na przykładzie rzeczywistych danych testowych. Dodatkowo badano optymalną politykę aktualizacji oprogramowania, jaką można prowadzić w ramach proponowanego paradygmatu. Słowa kluczowe: zależność błędów, niejednorodny proces Poissona, model wzrostu niezawodności oprogramowania, procesy detekcji i korekcji błędów oprogramowania IntroductionSoftware today plays important roles in almost every section of our society, and the software reliability has been a major concern in many integrated systems [3]. With continuous debugging, analysis and correction, the software reliability will grow gradually with testing [33]. During the past three decades, numerous software reliability growth models (SRGMs) have been proposed [2,7,24,26,35,40,41]. Among these models, Non-homogeneous Poisson Process (NHPP) models are the most commonly accepted [20,30,36,39,50]. Although NHPP models are mathematically tractable, they are developed under some strong assumptions on the software testing process. Specifically, NHPP models assume immediate fault removal and fault independency. To adapt to different practical software testing environments, generalizations of traditional models by relaxing the assumptions have been proposed [5,9,17,23,28,29].In practical software testing, each detected fault has to be reported, diagnosed, removed and verified before it can be noted as corrected. Consequently, the time spent for fault correction activity is not negligible. In fact, this debugging lag can be an important element in making decisions [16,49]. Therefore, it is necessary to incorporate the debugging lag into the modeling framework, i.e., to model both the fault detection process (FDP) and fault correcti...

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Selecting software reliability growth models and improving their predictive accuracy using historical projects data

Cited by 62 publications

References 26 publications

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The probability estimation of the electronic lesson implementation taking into account software reliability

Modeling of software fault detection and correction processes with fault dependency

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