Multi-release Software: An Approach for Assessment of Reliability Metrics from Field Data

  • Varuvel Antony Gratus
  • Xavier Pruno Pratibha
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8284)


With the ever increasing demands in requirements and dynamic scenario, the complexity of the software logics and hence the programming increased multi fold. Owing to this, the likelihood of the fault introduction during the development stages also increased, in spite of adherence to the software coding & management standards, verification, validation and testing procedures adopted. Incorporation of software based processing is more pronounced due to the complexity, compactness and very short reaction time warranted. The effect of faulty software would be unimaginably severe, leading to catastrophic events, especially for the case of safety critical applications. Hence, it is essential to quantify the risk associated with software. For the purposes of risk quantification, the reliability metrics of the software, typically inherent failure rate, to be known a-priori. The estimation of field failure rates of software, which is of multi-release in nature, will solely, depends on the systematic collection, segregation and categorization of data. In this paper, an approach to carry out pre-statistical analyses of data is presented from the perspective of assessment of reliability metrics of software.


Software reliability Reliability Metrics Failure Rate Risk Multi-Release Software 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Hu, Q.P., Peng, R., Xie, M., Ng, S.H., Levitin, G.: Software Reliability Modelling and Optimization for Multi-release Software Development Processes. In: Proceedings of the IEEE IEEM (2011)Google Scholar
  2. 2.
    Kapur, P.K., Pham, H., Aggarwal, A.G., Kaur, G.: Two Dimensional Multi-Release Software Reliability Modeling and Optimal Release Planning. IEEE Transactions on Reliability 61(3) (2012)Google Scholar
  3. 3.
    Jeske, D.R., Zhang, X., Pham, L.: Accounting for Realities When Estimating the Field Failure Rate of Software. In: IEEE Transactions on Reliability (2001)Google Scholar
  4. 4.
    Jeske, D.R., Qureshi, M.A.: Estimating the Failure Rate of Evolving Software Systems. In: Proceedings of ISSRE 2000, 11th International Symposium on Software Reliability Engineering (2000)Google Scholar
  5. 5.
    Mullen, R.E.: The Lognormal Distribution of Software Failure Rates Application to Software Reliability Growth Modeling. In: Proceedings of the Ninth International Symposium on Software Reliability Engineering (1998)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Varuvel Antony Gratus
    • 1
  • Xavier Pruno Pratibha
    • 2
  1. 1.Aeronautical Development AgencyBangaloreIndia
  2. 2.Alcatel-Lucent India LtdBangaloreIndia

Personalised recommendations