IDEAS home Printed from https://ideas.repec.org/h/spr/ssrchp/978-3-030-78919-0_2.html
   My bibliography  Save this book chapter

Software Reliability Growth Models Incorporating Software Project/Application’s Characteristics as a Power Function with Change Point

In: Optimization Models in Software Reliability

Author

Listed:
  • Shinji Inoue

    (Kansal University)

  • Abhishek Tandon

    (University of Delhi)

  • Prarna Mehta

    (University of Delhi)

Abstract

Software Reliability is a high-handed aspect to ascertain the quality of the system, which leads to development of tools that incorporates real time set-up. One of the real time concepts is change point, which highlights on the fact that a characteristic of the model changes during the testing time duration and it is significant to incorporate its effect in the model developed to ameliorate the reliability of the system. Moreover, faults are assumed to be independent and are incurred at any arbitrary time but, in practical world, faults may occur due to many factors like the testing environment, resource allocation, code complexity, testing team skill-set etc. This rate tends to change with time and assuming it to be constant may not reflect upon an actual output. Another conundrum that is taken care of is the release time of the software project/application. The weightage that is implied by this optimization planning is due to the fact that over testing may incur high cost to the firm whereas under testing may lead to release of a project/application with high fixing cost faults affecting the manufacturer by an elevated post-release cost. In this chapter, a framework is proposed that extends error-removal phenomenon model by encapsulating the software project/application characteristics as a parameter. A realistic software development situation is also taken in account by considering the parameter not only as a constant but a time dependent function. The suggested SRGMs are also monitored under a change point scenario, which gives real-time edge to the problem, and are then utilized to develop release time policy balancing reliability and expected cost incurred by a project/an application. The models are validated using Tandem dataset and performance measures are compared quantitatively with the standard models. On comparison of the results, the proposed model outperforms other extant models with and without change point.

Suggested Citation

  • Shinji Inoue & Abhishek Tandon & Prarna Mehta, 2022. "Software Reliability Growth Models Incorporating Software Project/Application’s Characteristics as a Power Function with Change Point," Springer Series in Reliability Engineering, in: Anu G. Aggarwal & Abhishek Tandon & Hoang Pham (ed.), Optimization Models in Software Reliability, pages 31-51, Springer.
    • Handle: RePEc:spr:ssrchp:978-3-030-78919-0_2
    DOI: 10.1007/978-3-030-78919-0_2
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:ssrchp:978-3-030-78919-0_2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.