IDEAS home Printed from https://ideas.repec.org/h/spr/ssrchp/978-3-030-43412-0_18.html
   My bibliography  Save this book chapter

Computational Intelligence Approaches for Software Quality Improvement

In: Reliability and Statistical Computing

Author

Listed:
  • Grigore Albeanu

    (“Spiru Haret” University)

  • Henrik Madsen

    (Danish Technical University)

  • Florin Popențiu-Vlădicescu

    (University Politehnica of Bucharest & Academy of Romanian Scientists)

Abstract

Obtaining reliable, secure and efficient software under optimal resource allocation is an important objective of software engineering science. This work investigates the usage of classical and recent development paradigms of computational intelligence (CI) to fulfill this objective. The main software engineering steps asking for CI tools are: product requirements analysis and precise software specification development, short time development by evolving automatic programming and pattern test generation, increasing dependability by specific design, minimizing software cost by predictive techniques, and optimal maintenance plans. The tasks solved by CI are related to classification, searching, optimization, and prediction. The following CI paradigms were found useful to help software engineers: fuzzy and intuitionistic fuzzy thinking over sets and numbers, nature inspired techniques for searching and optimization, bio inspired strategies for generating scenarios according to genetic algorithms, genetic programming, and immune algorithms. Neutrosophic computational models can help software management when working with imprecise data.

Suggested Citation

  • Grigore Albeanu & Henrik Madsen & Florin Popențiu-Vlădicescu, 2020. "Computational Intelligence Approaches for Software Quality Improvement," Springer Series in Reliability Engineering, in: Hoang Pham (ed.), Reliability and Statistical Computing, pages 305-317, Springer.
    • Handle: RePEc:spr:ssrchp:978-3-030-43412-0_18
    DOI: 10.1007/978-3-030-43412-0_18
    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:978-3-030-43412-0_18. 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.