IJCSNS International Journal of Computer Science and Network Security, VOL.10 No.5, May 2010 225 Manuscript received May 5, 2010 Manuscript revised May 20, 2010 Analysis of Relationships among Diverse Types of Software Attributes for Assessing Quality Factors of Gaming Software Mohammad Asif Ashraf Khan † , Mohammad Moinul Hoque †† and S. M. A. Al-Mamun ††† † Assistant Professor, Department of Computer Science and Engineering, Ahsanullah University of Science and Technology, Dhaka, Bangladesh †† Assistant Professor, Department of Computer Science and Engineering, Ahsanullah University of Science and Technology, Dhaka, Bangladesh ††† Professor, Department of Computer Science and Engineering, Ahsanullah University of Science and Technology, Dhaka, Bangladesh Summary The goal of this paper is to present a novel approach for assessment of the quality of Gaming software in terms of factors formulated by correlating its diversified attributes. All possible descriptive properties of customers, users and software products of the class Games were gathered under the three categories of ‘customer attributes’, ‘user attributes’ and ‘engineering attributes’. The attributes were then put into category to category correlation and reduced. Some feed backs from the environment of functioning of the system were also considered to verify the reduction procedure and use the attributes for the purpose. Key words: Software attributes, customer relationship management, gaming software, quality factors, quality assessment. 1. Introduction Quality Function Deployment (QFD) [1-2] or House of Quality (HQ) method has been proven to be a very useful tool for total quality management. The very idea underlying the method seems very interesting for the scope it provides. A product or service, when represented in a space defined by diverse types of attributes is provided with numerous avenues for getting assessed. Quality assessment itself is a difficult issue. And the problem with measurement of the features of a software product turns the problem of determining quality factors of it even harder. So, for quality factor assessment of gaming software we searched for effective methods and models that are in practice for marketing and management of other products. We thus came up with the idea of using QFD method. We assumed that a simple adaptation of the method to our problem may be very fruitful. In place of Engineering and Customer attribute correlation and perceptual modeling we propose an extension for more explicit processing. Besides, engineering and customer attributes we have proposed user attributes as well to capture in a more quantified way the factors down to the users of the product. And we have suggested to use numerical assessment values for correlating diverse types of attributes. Research activities of the computer community around Customer Relationship Management (CRM) were very inspiring for our efforts. A ‘Call for Papers’ for a special issue of IEEE Transaction on Knowledge and Data Engineering on ‘Customer Relationship Management’ that was planned to be published early 2007 is to be mentioned in this regard. Topics of interest of the issue and the computational challenges it highlighted were just attractive for explorative research. A number of research works on CRM is available, [3-5]. Study of the works opens some facts. Most important of those is that it is vital to take into consideration customer opinion in finding the quality factors measured in terms of product descriptors. Use of different attributes of products for quality assessment has its reference in different research works like [6-7]. We have explored the idea and proposed a procedure to quantify various attributes pragmatically. We finally come to the point at which we are able to describe the quality of gaming software in terms of its engineering attributes and recommend individual products to specific groups of gamers. And this idea has also its predecessor in [8]. 2. Gaming Software in Attribute Space In reference with the QFD method[1-2] we propose, with some enhancement, a methodology that involves three types of attributes to describe a product, namely, Engineering Attributes (EA), Customer Attributes (CA) and User Attributes (UA). Engineering Attributes are the attributes which show the characteristics of what is used. That is, for instance, we can define a product in terms of EA, measurable features popular to the designers and manufacturers of the product. Customer Attributes reflect