Intelligent software quality model using feature ranking technique

• Main Authors: Yahaya, Jamaiah, Deraman, Aziz, Kamaruddin, Siti Sakira, Ahmad, Ruzita
• Format: Article
• Language: English
• Published: Advanced Institutes of Convergence Information Technology 2013
• Subjects: QA76 Computer software
• Online Access: http://repo.uum.edu.my/15353/1/b119a.pdf; http://repo.uum.edu.my/15353/; http://www.globalcis.org/ijact/home/index.html

This paper presents an intelligent software quality model using feature ranking technique for the purpose of dynamically selecting the appropriate attributes for software quality assessment.The existing software quality models only support static set of attributes and do not include the dynamic and intelligent attributes selection process.The model also known as i-PQF has a capability to learn from previous experience.The proposed feature ranking technique (FRT) adopts both the filter and wrapper approach to learn and rank quality attributes as new software quality assessment data are added to the database.A ranking model named Most Priority of Features (MPF) is introduced to perform the ranking.The issue of redundancy during ranking is addressed using classifiers that are able to learn the most suitable attributes from existing data. Evaluation of the proposed technique is performed through comparison with similar technique in the area and the results shows that our technique performs better in terms of correlation to human judgment.