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Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
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Updated: May 10, 2025

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A software reliability model for open source big data systems based on Weibull-Weibull distribution.

Jinyong Wang1, Haijun Geng2, Pengda Li2

  • 1School of Automation and Software Engineering, Shanxi University, Taiyuan, People's Republic of China. wjy@sxu.edu.cn.

Scientific Reports
|April 26, 2025
PubMed
Summary

This study introduces a new software reliability model for big data systems. The Weibull-Weibull model accurately predicts remaining faults, aiding developers in assessing open-source big data software reliability.

Keywords:
Open source big data systemSoftware reliability modelWeibull–Weibull distribution

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Area of Science:

  • Computer Science
  • Software Engineering
  • Data Science

Background:

  • Big data technologies are increasingly integrated into production and daily life.
  • Software reliability for big data systems is a critical but under-researched area.
  • Open-source big data software often exhibits a rise in errors during later testing phases.

Purpose of the Study:

  • To propose a novel software reliability model for big data systems.
  • To address the gap in research concerning reliability modeling and assessment for big data software.
  • To improve the prediction of remaining faults in open-source big data systems.

Main Methods:

  • Development of a software reliability model based on a Weibull-Weibull distribution.
  • Empirical validation of the proposed model using experimental data.
  • Assessment of the model's accuracy in predicting remaining software faults.

Main Results:

  • The proposed Weibull-Weibull model demonstrated effectiveness in reliability assessment.
  • Experimental results confirmed the model's accuracy in predicting remaining faults.
  • The model provides a reliable method for evaluating software quality in big data development.

Conclusions:

  • The developed model enhances the assessment of software reliability for big data systems.
  • This research contributes a valuable tool for developers working with open-source big data software.
  • Accurate fault prediction aids in delivering more reliable big data solutions.