A Comprehensive Review on Software Reliability Growth Models utilizing Soft Computing Approaches

Lohmor, Shailee; Sagar, Bharat Bhushan

doi:10.1007/978-3-319-47952-1_40

Advances in Intelligent Systems and Computing

2016

DOI: 10.1007/978-3-319-47952-1_40

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A Comprehensive Review on Software Reliability Growth Models utilizing Soft Computing Approaches

Shailee Lohmor

Bharat Bhushan Sagar²

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Cited by 2 publications

References 30 publications

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Advancing software reliability with time series insights: A non‐autoregressive ANN approach

Sharma,

Rana

2024

Quality & Reliability Eng

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Software reliability is a critical factor in assessing the health of software and identifying defects. Software reliability growth models (SRGM) are used to estimate the occurrence of software faults. There are various parameterized and non‐parameterized models of SRGM. These models effectively predict fault occurrence for limited testing conditions. To resolve this problem various neural and artificial neural network (ANN) models are proposed. A problem while using ANN is over‐fitting and under‐fitting. Non‐autoregressive time series models, including ANN variants, offer promising solutions to address under‐fitting issues in SRGM, providing enhanced predictive capabilities for fault occurrence across diverse testing conditions. This study proposes a modified version with a Bayesian regularization technique to address over‐fitting. This modification aims to enhance the suitability of the Bayesian regularization framework for nonlinear autoregressive (NAR) models by carefully adjusting regularization parameters. Comprehensive testing with real‐world software failure datasets is conducted to evaluate the effectiveness of the proposed approach. The results demonstrate that our modified approach improved generalization capabilities and increased prediction accuracy. The NAR‐ANN model exhibits a lower mean squared error of 0.12935 and a higher value of 0.99853.

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Advancing software reliability with time series insights: A non‐autoregressive ANN approach

Sharma,

Rana

2024

Quality & Reliability Eng

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Soft Computing and Decision Support System for Software Process Improvement: A Systematic Literature Review

Xiaolong

Zhao

Zhong

et al. 2021

Scientific Programming

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Software project development is very crucial, and measuring the exact cost and effort of development is becoming tedious and challenging. Organizations are trying to wind up their project of software development within the agreed budget and schedule successfully. Traditional practices are inadequate to achieve the current needs of the software industry. Underestimation and overestimation of software development effort lead to financial implications in the form of resources, cost of staffing, and budget of developing the software project. Soft computing (SC) approaches and tools deliver an addition of techniques for anticipating resistance to the deception, defect, incomplete truth for traceability and ambiguity, low arrangement cost, and strength. A large amount of SC approaches is prevailing in the literature to accomplish way-out to difficulties precisely, practically, and speedily. The approaches of SC can give better prediction, high performance, and dynamic behavior. SC deals with computational intelligence which integrates the concept of agent paradigm and SC. The proposed study presents a systematic literature review (SLR) of the approaches, tools, and techniques of SC used in the literature. The study presented a comprehensive review by searching the defined keywords in the popular libraries, filtered the paper, and obtained most relevant papers. After the selection of the papers, the quality assessment process of the included papers has been done in order to determine the relevancy of the papers. The study will help researchers in the area of research to devise novel ideas and solutions to overcome the existing issue on the basis of this study as evidence of the literature.

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A Comprehensive Review on Software Reliability Growth Models utilizing Soft Computing Approaches

Cited by 2 publications

References 30 publications

Advancing software reliability with time series insights: A non‐autoregressive ANN approach

Advancing software reliability with time series insights: A non‐autoregressive ANN approach

Soft Computing and Decision Support System for Software Process Improvement: A Systematic Literature Review

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