IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v8y2017i2d10.1007_s13198-016-0419-1.html
   My bibliography  Save this article

Generating and evaluating effectiveness of test sequences using state machine

Author

Listed:
  • Vikas Panthi

    (National Institute of Technology)

  • Durga Prasad Mohapatra

    (National Institute of Technology)

Abstract

The aim of this paper is to generate test sequences for object-oriented software with composite states using state machines. This experimental work in software testing focuses on generating test sequences using the proposed algorithm called SMTSG (State Machine to Test Sequence Generation). This work also describes the effectiveness of test sequences by using mutation analysis. Our approach considers nine types of state faults for checking the efficiency of the generated test sequences. The effectiveness of the prioritized test sequences is shown using Average Percentage Fault Detection (APFD) metric. The experimental results show that the test sequences generated using our proposed approach are more efficient than the existing approaches.

Suggested Citation

  • Vikas Panthi & Durga Prasad Mohapatra, 2017. "Generating and evaluating effectiveness of test sequences using state machine," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 242-252, June.
  • Handle: RePEc:spr:ijsaem:v:8:y:2017:i:2:d:10.1007_s13198-016-0419-1
    DOI: 10.1007/s13198-016-0419-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-016-0419-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s13198-016-0419-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    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:ijsaem:v:8:y:2017:i:2:d:10.1007_s13198-016-0419-1. 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.