IDEAS home Printed from https://ideas.repec.org/a/ids/ijidsc/v2y2010i3p233-272.html
   My bibliography  Save this article

The application of intelligent and soft-computing techniques to software engineering problems: a review

Author

Listed:
  • Ramakanta Mohanty
  • Vadlamani Ravi
  • Manas Ranjan Patra

Abstract

This paper presents a comprehensive review of the work done during 1990-2008 in the application of intelligent techniques to solve software engineering (SE) problems. The review is categorised according to the type of intelligent technique applied viz. (1) neural networks (NNs), (2) fuzzy logic, (3) genetic algorithm, (4) decision tree, (5) case base reasoning and (6) other techniques subsuming soft computing. Further, the source of the data set and the results whenever available are also provided. We find that NNs is the most often used non-parametric method in SE and there exists immense scope to apply other equally famous methods such as fuzzy logic, decision trees and rough sets. The review is going to be useful to researchers as a starting point as it provides important future research directions. For practitioners also, the review would be useful. This would eventually lead to better decision making in SE thereby ensuring better, more reliable and cost effective software products.

Suggested Citation

  • Ramakanta Mohanty & Vadlamani Ravi & Manas Ranjan Patra, 2010. "The application of intelligent and soft-computing techniques to software engineering problems: a review," International Journal of Information and Decision Sciences, Inderscience Enterprises Ltd, vol. 2(3), pages 233-272.
    • Handle: RePEc:ids:ijidsc:v:2:y:2010:i:3:p:233-272
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=33450
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Joshua Steakelum & Jacob Aubertine & Kenan Chen & Vidhyashree Nagaraju & Lance Fiondella, 2022. "Multi-phase algorithm design for accurate and efficient model fitting," Annals of Operations Research, Springer, vol. 311(1), pages 357-379, April.

    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:ids:ijidsc:v:2:y:2010:i:3:p:233-272. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=306 .

    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.