IDEAS home Printed from https://ideas.repec.org/a/bco/mbraaa/v7y2020p11-23.html
   My bibliography  Save this article

An Empirical Evaluation of Requirements Prioritization Techniques

Author

Listed:
  • Naila Jan

    (SERL, National University of Computer and Emerging Sciences, Islamabad, Pakistan)

  • Irum Inayat

    (SERL, National University of Computer and Emerging Sciences, Islamabad, Pakistan)

  • Muhammad Abbas

    (RISE SICS, Research Institutes of Sweden, Västerås, Sweden)

Abstract

In today’s time and budget intensive software development market, quick delivery is the basic motive of teams. Software development teams strive to gain customer satisfaction by all possible means. Requirements prioritization is the most challenging customer input dependent task in the software development life cycle that decides the fate of a project. Selection of a well-suited requirements prioritization technique may result in customer satisfaction and on time delivery time. Literature reports on many requirements prioritization techniques in practice. However, each has its own features that can outperform the rest for a certain case. Therefore, this research is conducted to empirically evaluate the existing techniques in terms of certain quality measures (i.e., accuracy, efficiency, and scalability). The selected techniques are evaluated for the small, medium and large scale of requirements sets. For that, we selected five existing techniques that are multi-criteria-decision-making techniques and have user involvement (i.e., Analytical Hieratical Process (AHP), Analytical Network Process (ANP), FuzzyAHP, FuzzyANP and Interactive Genetic Algorithm (IGA)). The experimental results showed that among the five selected techniques, FuzzyAHP is the most efficient and accurate technique for the large dataset of requirements.

Suggested Citation

Handle: RePEc:bco:mbraaa::v:7:y:2020:p:11-23
DOI: 10.33844/mbr.2020.60322
as

Download full text from publisher

File URL: https://api.eurokd.com/Uploads/Article/863/mbr.2020.60322.pdf
Download Restriction: no

File URL: https://libkey.io/10.33844/mbr.2020.60322?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
---><---

More about this item

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:bco:mbraaa::v:7:y:2020:p:11-23. 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: Sara Gunen (email available below). General contact details of provider: .

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.