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

Yahya M. Tashtoush, D. Darwish, Motasim Albdarneh, I. Alsmadi, Khalid Alkhatib
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引用次数: 7

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. A Business Classifier to Detect Readability Metrics on Software Games and Their Types
用于检测软件游戏及其类型的可读性指标的业务分类器
可读性指标被认为是影响游戏业务的最重要因素之一,可以用来评估游戏的总体质量和可用性。由于游戏可能会经历许多演变,并由许多开发者开发,代码可读性会显著影响创建、更新或维护此类游戏所需的时间和资源。本文介绍了一种检测桌面和移动环境下用Java或c++编写的游戏可读性的新方法。基于数据挖掘技术,提出了一种基于可读性和其他软件指标或属性来预测游戏类型的方法。另一个分类器是基于收集到的几个特征来预测游戏应用程序中的软件可读性。这些分类器是使用WEKA数据挖掘工具中可用的机器学习算法(J48决策树,支持向量机,支持向量机和朴素贝叶斯,NB)构建的。用于检测软件游戏及其类型的可读性指标的业务分类器
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