Big Data-Enabled Frameworks for Software Reliability Assessment

Authors

  • Syed Waqar Jaffry Department of Information Technology University of the Punjab, Lahore, Pakistan
  • Irfan Ahmed Department of Computer Science University of Sialkot, Sialkot, Pakistan
  • Hurriya Fahad Department of Computer Science University of Sialkot, Sialkot, Pakistan

Keywords:

Big Data, Software Reliability, Predictive Analytics, Machine Learning, Real-Time Monitoring, Open-Source Software, Fault Prediction, Reliability Assessment

Abstract

The increasing complexity and scale of modern software systems necessitate advanced methodologies for assessing software reliability. Traditional reliability models often fall short in capturing the dynamic nature of big data environments. This paper proposes an integrated framework that leverages big data analytics to enhance software reliability assessment. By incorporating real-time data streams, machine learning algorithms, and predictive analytics, the framework offers a comprehensive approach to monitor, evaluate, and improve software reliability. The proposed model is validated using case studies from open-source big data platforms, demonstrating its efficacy in real-world scenarios.

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Published

2022-12-31

Issue

Jul-Dec 2022

Section

Articles

License

All articles published in the International Journal of Advanced Sciences and Computing (IJASC) are open access and licensed under the Creative Commons Attribution (CC BY 4.0) license. Authors retain copyright, and users may read, share, reuse, and adapt the content with proper attribution.