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SDE Based SRGM Considering Irregular Fluctuation in Fault Introduction Rate

In: Predictive Analytics in System Reliability

Author

Listed:
  • Deepika

    (University of Delhi)

  • Adarsh Anand

    (University of Delhi)

  • Shinji Inoue

    (Kansai University)

  • Prashant Johri

    (Galgotias University)

Abstract

Software debugging is complicated and can be considered as stochastic in nature. During fault removal, debuggers at-times introduce new faults. Thereafter, the fault introduction process can be said to be non-linear in nature. In this study, we have proposed a software reliability growth model considering the irregular fluctuation of fault introduction rate over time with non-constant fault detection rate. We assume that fault introduction changes non-linearly over time and the fault introduction rate fluctuates irregularly. Ito’s process is used for solving the differential equation to find the analytical solution. The model is fitted on two real world data sets from two open-source project: Mozilla and Gnome. The experimental findings show that present model exhibit estimation result and having strong prediction skill.

Suggested Citation

  • Deepika & Adarsh Anand & Shinji Inoue & Prashant Johri, 2023. "SDE Based SRGM Considering Irregular Fluctuation in Fault Introduction Rate," Springer Series in Reliability Engineering, in: Vijay Kumar & Hoang Pham (ed.), Predictive Analytics in System Reliability, pages 67-80, Springer.
    • Handle: RePEc:spr:ssrchp:978-3-031-05347-4_5
    DOI: 10.1007/978-3-031-05347-4_5
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