IDEAS home Printed from https://ideas.repec.org/h/spr/ssrchp/978-3-031-55048-5_9.html
   My bibliography  Save this book chapter

Bug Prediction Techniques: Analysis and Review

In: Reliability Engineering for Industrial Processes

Author

Listed:
  • Riya Sen

    (Jawaharlal Nehru University)

  • V. B. Singh

    (Jawaharlal Nehru University)

Abstract

Bug expectation could be a preparation where we attempt to foresee bugs based on authentic information about the specific application. The term distinguishes “bug hot spots” within the code base and banners as segments of code that, when adjusted, truly come about in many bugs. We have discussed various techniques for predicting bugs during the last two decades. Therefore, there is a need to know the models of research that summarise and compare techniques on different datasets. We present a complete catalogue of all known techniques in this paper. We found many techniques as a result of our study. They also support a variety of datasets, including Eclipse, Mozilla and Gnome, Bugzilla and others. We categorise different techniques to predict the models in this study based on their type, availability, model techniques, identified bugs, supported datasets, and main features.

Suggested Citation

  • Riya Sen & V. B. Singh, 2024. "Bug Prediction Techniques: Analysis and Review," Springer Series in Reliability Engineering, in: P. K. Kapur & Hoang Pham & Gurinder Singh & Vivek Kumar (ed.), Reliability Engineering for Industrial Processes, pages 137-143, Springer.
  • Handle: RePEc:spr:ssrchp:978-3-031-55048-5_9
    DOI: 10.1007/978-3-031-55048-5_9
    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:978-3-031-55048-5_9. 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.