A new fuzzy rule based algorithm for estimating software faults in early phase of development

Chatterjee, Saikat; Maji, Bappa

doi:10.1007/s00500-015-1738-x

Cited by 30 publications

(7 citation statements)

References 44 publications

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“…In 2016, Chatterjee and Maji 105 developed a fuzzy logic‐based prediction model using a phase rule generating base algorithm. This model uses software metrics criteria information from requirements analysis phase, estimated software size and expert opinion.…”

Section: Research Backgroundmentioning

confidence: 99%

Software reliability prediction: A survey

Oveisi

Moeini

Mirzaei

et al. 2022

Quality & Reliability Eng

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Softwares play an important role in controlling complex systems. Monitoring the proper functioning of the components of such systems is the principal role of softwares. Often, a petite fault in one of the subsystems may cause irreparable damages; therefore, it is of great importance to be able to predict software faults and estimate the reliability of softwares. In this survey, we present a classification of various methods proposed in the literature to predict software reliability. This study summarizes the results of more than 200 research papers in the field. We also discuss the challenges involved in prediction methods along with proposed partial solutions (i.e., Bayesian methods) to improve the accuracy of such predictions. Moreover, we review numerous evaluation measures introduced so far to assess the performance of prediction models, the datasets they are based on, and also the results they yield.

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Section: Research Backgroundmentioning

confidence: 99%

Software reliability prediction: A survey

Oveisi

Moeini

Mirzaei

et al. 2022

Quality & Reliability Eng

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“…Authors in [11] explore how the estimation of risk at the early stages of software development affects reliability and software cost. The study suggests a new fuzzy rule base algorithm for the validation of the proposed fuzzy rule base model while data of 20 actual software projects have been used.…”

Section: IImentioning

confidence: 99%

Software Risk Analysis with the use of Classification Techniques: A Review

Khan¹,

Mirza

Saleem

2020

Eng. Technol. Appl. Sci. Res.

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Risk analysis and management is a critical aspect of the software development process. Various risks are associated with every phase of the software development lifecycle. The early identification of risks in each phase of software development coupled with mitigating plans can help to reduce the cost of the product and increase software quality. This study aims to explore various tools and techniques used in the literature of analyzing and managing risks. Most risk analysis techniques have been applied in the requirement analysis phase, so there is a scarcity of tools supporting automated risk analysis. Accommodating various types of risk factors to predict the software risks reduces the accuracy of the classifier.

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“…Reliability-related metrics have been used to predict faults by Pandey & Goyal (Pandey and Goyal 2013). Chatterjee and Maji (Chatterjee and Maji 2016), have proposed a novel algorithm to generate a fuzzy rule base for predicting faults at the requirement phase of software development. Smidts et al (Smidts et al 1998), have proposed a model based on Bayesian statistics for fault prediction.…”

Section: Introductionmentioning

confidence: 99%

Neutrosophic Classifier-based Algorithm for Dependability Analysis in Early Phase of Software Development

Chatterjee

Saha

Yadav

et al. 2023

Preprint

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Due to the significant dependency on software, the enhancement of dependability in software attributes is the most challenging issue for software developers. The dependability attributes like: reliability, performability, security, safety, risk, maintainability perform important roles for the development of dependable software. The present study proposes a new algorithm to predict more faults efficiently in the requirement phase to assess the dependability of the software systems. Here three dependability attributes like: performability, reliability, and security, have been considered to develop the proposed model. Neutrosophic logic can be a useful tool to handle impreciseness, incompleteness of software metric values by its three independent components like: truth, indeterminate, and false components. Based on expert knowledge most important four requirement phase metrics have been considered here as input for the model development. The performance of the proposed model has been validated based on real software project data. The proposed model have been compared with different other fault prediction models by comparison criteria. The performance of the proposed model is better and it can predict more faults than other models. Software organizations can use the proposed model for the requirement phase fault count and construct dependable software.

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A new fuzzy rule based algorithm for estimating software faults in early phase of development

Cited by 30 publications

References 44 publications

Software reliability prediction: A survey

Software reliability prediction: A survey

Software Risk Analysis with the use of Classification Techniques: A Review

Neutrosophic Classifier-based Algorithm for Dependability Analysis in Early Phase of Software Development

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