IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-319-00209-5_11.html
   My bibliography  Save this book chapter

Harmonizing the Babel of Voices

In: Conversations About Challenges in Computing

Author

Listed:
  • Aslak Tveito

    (Simula Research Laboratory)

  • Are Magnus Bruaset

    (Simula Research Laboratory)

Abstract

Modern-day computers and processors are too complicated for a human to understand. Software engineers frequently reuse and patch existing code rather than starting from scratch, but this eventually leads to the accretion of multigenerational code of great opacity whose behaviour no one can fully predict. One troubleshooting technique that software engineers often apply is machine learning: in essence, using machines to diagnose the faults in other machines. A machine learning program will test the response of a new piece of software to many different combinations of inputs and look for patterns in the results that suggest how the software may be flawed. It is really doing the same thing a human would do – learning from the past to predict the future – but a computer can try many more combinations and can detect more deeply hidden patterns than a human can.

Suggested Citation

  • Aslak Tveito & Are Magnus Bruaset, 2013. "Harmonizing the Babel of Voices," Springer Books, in: Are Magnus Bruaset & Aslak Tveito (ed.), Conversations About Challenges in Computing, edition 127, chapter 11, pages 85-91, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-00209-5_11
    DOI: 10.1007/978-3-319-00209-5_11
    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
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:sprchp:978-3-319-00209-5_11. 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.