Suitability analysis of software reliability models for its applicability on NPP systems

Kumar, Pratap; Singh, Lalit Kumar; Kumar, Chiranjeev

doi:10.1002/qre.2315

Cited by 11 publications

(6 citation statements)

References 49 publications

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“…Deterministic models contain two sub-categories: the Halstead model and McCabe's Cyclomatic Complexity models, and both will discuss in detail in the next section. On the other hand, probabilistic models contain ten sub-categories [16]:…”

Section: Related Workmentioning

confidence: 99%

“…• Deterministic models analyze the program source code, use the result as input, and do not combine any random events or values. For example, Halstead Model and McCabe's Cyclomatic Complexity V(G) Models [16].…”

Section: Introductionmentioning

confidence: 99%

“…• Probabilistic models describe error correction and failure cases as random events. For example, Error Seeding, Reliability Growth, Failure Rate, Input Domain, Program Structure [16].…”

Section: Introductionmentioning

confidence: 99%

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Reliability Assessment for Open-Source Software Using Deterministic and Probabilistic Models

Ramadan¹,

Harb²,

Mousa³

et al. 2022

IJITCS

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Nowadays, computer software plays a significant role in all fields of our life. Essentially open-source software provides economic benefits for software companies such that it allows building new software without the need to create it from scratch. Therefore, it is extremely used, and accordingly, open-source software’s quality is a critical issue and one of the top research directions in the literature. In the development cycles of the software, checking the software reliability is an important indicator to release software or not. The deterministic and probabilistic models are the two main categories of models used to assess software reliability. In this paper, we perform a comparative study between eight different software reliability models: two deterministic models, and six probabilistic models based on three different methodologies: perfect debugging, imperfect debugging, and Gompertz distribution. We evaluate the employed models using three versions of a standard open-source dataset which is GNU’s Not Unix Network Object Model Environment projects. We evaluate the employed models using four evaluation criteria: sum of square error, mean square error, R-square, and reliability. The experimental results showed that for the first version of the open-source dataset SRGM-4 based on imperfect debugging methodology achieved the best reliability result, and for the last two versions of the open-source dataset SRGM-6 based on Gompertz distribution methodology achieved the best reliability result in terms of sum of square error, mean square error, and R-square.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Reliability Assessment for Open-Source Software Using Deterministic and Probabilistic Models

Ramadan¹,

Harb²,

Mousa³

et al. 2022

IJITCS

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show abstract

“…The reader will find it easier to understand with a minimum amount of effort. However, there are few papers 8,9 in the literature that present state-of-the-art reviews, but they are more centred on NPP. The paper is organized as follows: Section 2 discusses the methodology of literature review.…”

Section: Introductionmentioning

confidence: 99%

“…Yacoub et al 28 30 Tu et al 53 6 Bearfield et al 29 31 Singh and Rajput 54 7 Huang et al 30 32 Jia et al 55 8 Dutuit and Rauzy 32 33 Singh et al 56 9 Chang et al 31 34 Yu and Jie 63 10 Mihalache et al 33 35 Kumar et al 57 11 Wende et al 34 36 Vicenzutti et al 58 12 Shalev and Tiran 35 37 Kaur et al 59 13 Chen et al 36 38 Chi et al 60 14 Kumar and Misra 37 39 Wang et al 61 15 Guo and Yang 38 40 Wu and Schnieder 62 16 Bucci et al 39 17 Chew et al 40 18 Aljazzar et al 41 19 Volkanovski et al 42 20 Kumar and Jackson 43 21 Cai et al 44 22 Tuan et al 45 23 Ramos et al 46 24 Kleyner and Volovoi …”

mentioning

confidence: 99%

Reliability of safety‐critical systems: A state‐of‐the‐art review

Maurya

Kumar

2020

Quality & Reliability Eng

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Safety-critical systems are designed to prevent catastrophic consequences from failure, such as injury or death to humans and environmental damage. These must be carefully designed to ensure reliability requirements. The purpose of this paper is to identify the number of models in the reliability analysis of safety-critical systems. To achieve this goal, we conducted a systematic review of 40 shortlisted studies. The selected studies are classified based on various techniques used in safety-critical systems. This paper summarizes the literature review in the field of reliability of safety-critical systems. The limitations of the literature are exquisitely represented. The international safety norms and applications of safety-critical systems are discussed systematically in this paper. This paper emerges research trends, research challenges and insights of the researcher for future research direction in the area of safety-critical systems.

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Availability analysis of safety-critical and control systems of NPP using stochastic modeling

Kumar

Singh

Chaudhari

et al. 2020

Annals of Nuclear Energy

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Suitability analysis of software reliability models for its applicability on NPP systems

Cited by 11 publications

References 49 publications

Reliability Assessment for Open-Source Software Using Deterministic and Probabilistic Models

Reliability Assessment for Open-Source Software Using Deterministic and Probabilistic Models

Reliability of safety‐critical systems: A state‐of‐the‐art review

Availability analysis of safety-critical and control systems of NPP using stochastic modeling

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