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IJMLC 2013 Vol.3(5): 393-395 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2013.V3.346

Estimation of the New Agile XP Process Model for Medium-Scale Projects Using Industrial Case Studies

M. Rizwan Jameel Qureshi

Abstract—Agile is one of the terms with which software professionals are quite familiar. Agile models promote fast development to develop high quality software. XP process model is one of the most widely used and most documented agile models. XP model is meant for small-scale projects. Since XP model is a good model, therefore there is need of its extension for the development of medium and large-scale projects. XP model has certain drawbacks such as weak documentation and poor performance while adapting it for the development of medium and large-scale projects having large teams. A new XP model is proposed in this paper to cater the needs of software development companies for medium-scale projects having large teams. This research may prove to be step forward for adaptation of the proposed new XP model for the development of large-scale projects. Two independent industrial case studies are conducted to validate the proposed new XP model handling for small and medium scale software projects, one case study for each type of project.

Index Terms—Agile, XP, refactoring, TDD.

The author was with COMSATS Institute of Information Technology, Lahore, Pakistan. He is now with the department of Information Technology, Faculty of Computing & Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia (e-mail: anriz@ hotmail.com).


Cite:M. Rizwan Jameel Qureshi, "Estimation of the New Agile XP Process Model for Medium-Scale Projects Using Industrial Case Studies," International Journal of Machine Learning and Computing vol.3, no. 5, pp. 393-395, 2013.

General Information

  • ISSN: 2010-3700 (Online)
  • Abbreviated Title: Int. J. Mach. Learn. Comput.
  • Frequency: Bimonthly
  • DOI: 10.18178/IJMLC
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.
  • E-mail: ijmlc@ejournal.net

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