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Experiences with Extreme Programming

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Sherrell, L., Krishna, B., Velaga, N., Vejandla, P. & Satharla, M. (2010). Experiences with Extreme Programming. Journal of Computers in Mathematics and Science Teaching, 29(3), 247-268. Chesapeake, VA: AACE.
Retrieved from http://www.editlib.org/p/33162.

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Journal Information

JCMST

Journal of Computers in Mathematics and Science Teaching
ISSN 0731-9258
Volume 29, Issue 3, August 2010
Association for the Advancement of Computing in Education (AACE)  Chesapeake, VA

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Authors

Linda Sherrell, Bhagavathy Krishna, Natasha Velaga, Pavan Vejandla, Mahesh Satharla, University of Memphis, United States

Abstract

*** Invited as a paper from ED-MEDIA 2009 *** Agile methodologies have become increasingly popular among software developers as evidenced by industrial participation at related conferences. The popularity of agile practices over traditional techniques partly stems from the fact that these practices provide for more customer involvement and better accommodate rapidly changing requirements, both of which are important in the current Internet-focused environment. This article describes the design and implementation of an independent study in agile software development methodologies. In this course, graduate students in computer science compared traditional software development life cycle models and their associated practices with those of agile methodologies. Students were introduced to Extreme Programming (XP), one of the best-known agile methodologies, by implementing a computer game. Then the students performed a literature review on one or more agile practices. Finally, they introduced XP into their respective research groups (wireless sensor networks, intelligent tutoring systems, and genetic algorithms). This article is a reflection of their experiences, along with those of the instructor. It should prove beneficial to two groups of educators: instructors who want to teach a course in agile methodologies and those individuals who develop their own software and want to learn a lightweight process model.

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