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Predicting Total Number of Failures in a Software Using NHPP Software Reliability Growth Models

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Proceedings of the Third International Conference on Soft Computing for Problem Solving

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 259))

Abstract

For a software development project, management often faces the dilemma of when to stop testing the software and release it for operation. Estimating the remaining defects (or failures) in software can help test management to make release decisions. Several methods exist to estimate the defect content in software; among them are also a variety of software reliability growth models (SRGMs). SRGMs have underlying assumptions that are often violated in practice, but empirical evidence has shown that a number of models are quite robust despite these assumption violations. However it is often difficult to know which model to apply in practice. In the present study a method for selecting SRGMs to predict total number of defects in a software is proposed. The method is applied to a case study containing 3 datasets of defect reports from system testing of three releases of a large medical record system to see how well it predicts the expected total number of failures in a software.

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Abbreviations

m(t):

mean value function

a(t):

error content function

b(t):

error detection rate per error at time t

N(t):

random variable representing the cumulative number of software errors predicted by time t

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Authors and Affiliations

  1. Thapar University, Patiala, 147004, India

    Poonam Panwar & A. K. Lal

Authors
  1. Poonam Panwar
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  2. A. K. Lal
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Correspondence to Poonam Panwar .

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Editors and Affiliations

  1. Department of Paper Technology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Millie Pant

  2. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Kusum Deep

  3. Department of Mathematics and Computer Science, Liverpool Hope University, Liverpool, United Kingdom

    Atulya Nagar

  4. Department of Applied Mathematics, South Asian University, New Delhi, India

    Jagdish Chand Bansal

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Panwar, P., Lal, A.K. (2014). Predicting Total Number of Failures in a Software Using NHPP Software Reliability Growth Models. In: Pant, M., Deep, K., Nagar, A., Bansal, J. (eds) Proceedings of the Third International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 259. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1768-8_62

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  • DOI: https://doi.org/10.1007/978-81-322-1768-8_62

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  • Print ISBN: 978-81-322-1767-1

  • Online ISBN: 978-81-322-1768-8

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