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Nonhomogeneous Poisson process software reliability model incorporating initial fault diversification and dependent

Youn Su Kim1, Kwang Yoon Song1,2, Hoang Pham3

  • 1Institute of Well-Aging Medicare and CSU G-LAMP Project Group, Chosun University, Gwangju, Republic of Korea.

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Summary
This summary is machine-generated.

This study introduces a new software reliability model that accounts for initial defects and dependent failures. It outperforms traditional models, enhancing real-world software reliability predictions.

Keywords:
Nonhomogeneous Poisson processdependent failuresinitial faultssoftware reliability model

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Area of Science:

  • Computer Science
  • Software Engineering

Background:

  • Software systems are increasingly complex and vital, necessitating robust reliability measures.
  • Existing software reliability models often assume zero initial defects, limiting their real-world applicability.

Purpose of the Study:

  • To develop and validate a novel software reliability model that incorporates initial defects and dependent failure occurrences.
  • To improve the accuracy of software failure prediction, especially in the early stages of development.

Main Methods:

  • A new software reliability model was developed, assuming both independent and dependent failure processes.
  • The proposed model was evaluated against 15 traditional models using three distinct datasets.
  • Performance was assessed using nine different evaluation criteria.

Main Results:

  • The proposed model demonstrated superior performance across all tested datasets compared to traditional models.
  • The model effectively predicts software failures by considering initial defect presence.
  • The model's ability to handle dependent failures enhances its predictive power.

Conclusions:

  • The developed software reliability model offers a significant advancement for predicting failures in complex software.
  • This research contributes to creating more accurate and applicable software reliability models for real-world scenarios.
  • Understanding early-stage defects is crucial for improving overall software dependability.