A Business Classifier to Detect Readability Metrics on Software Games and Their Types

Yahya M. Tashtoush, Derar Darwish, Motasim Albdarneh, Izzat M. Alsmadi and Khalid Alkhatib
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Yahya M. Tashtoush: Department of Computer Science, Computer and Information Technology Faculty, Jordan University of Science and Technology (JUST), Irbid, Jordan
Derar Darwish: Department of Computer Science, Computer and Information Technology Faculty, Jordan University of Science and Technology (JUST), Irbid, Jordan
Motasim Albdarneh: Department of Computer Science, Computer and Information Technology Faculty, Jordan University of Science and Technology (JUST), Irbid, Jordan
Izzat M. Alsmadi: Department of Information Systems, Prince Sultan University, Riyadh, Kingdom of Saudi Arabia
Khalid Alkhatib: Department of Computer Information Systems, Computer and Information Technology Faculty, Jordan University of Science and Technology (JUST), Irbid, Jordan

International Journal of E-Entrepreneurship and Innovation (IJEEI), 2013, vol. 4, issue 4, 47-57

Abstract: Readability metric is considered to be one of the most important factors that may affect games business in terms of evaluating games' quality in general and usability in particular. As games may go through many evolutions and developed by many developers, code readability can significantly impact the time and resources required to build, update or maintain such games. This paper introduces a new approach to detect readability for games built in Java or C++ for desktop and mobile environments. Based on data mining techniques, an approach for predicting the type of the game is proposed based on readability and some other software metrics or attributes. Another classifier is built to predict software readability in games applications based on several collected features. These classifiers are built using machine learning algorithms (J48 decision tree, support vector machine, SVM and Naive Bayes, NB) that are available in WEKA data mining tool.

Date: 2013
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