An Approach for Analyzing ISO / IEC 25010 Product Quality Requirements based on Fuzzy Logic and Likert Scale for Decision Support Systems
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2016, Vol 7, Issue 12
Abstract
Decision Support Systems (DSS) are collaborative software systems that are built to support controlling of an organization in decision making process when faced with non-routine problems in a specific application domain. It’s important to measure portability, maintainability, security, reliability, functional suitability, performance efficiency, compatibility, and usability quality requirements of DSS properly. ISO / IEC 25010 which replaced ISO 9126, used for three different quality models for software products, such as: a) Quality in use model, b) Product quality model, and c) Data quality model. There is a lack of methodologies to measure and quantify these quality requirements. Fuzzy logic used to specify quality requirements of DSS, because it’s an approach to computing based on degrees of truth, rather than true or false logics. Likert scale is a method in which it converts qualitative values into quantitative values to make a best statistical analysis. The measurement and quantification of quality requirements of DSS is a challenging task, because these quality requirements are in qualitative form and can’t be represented in quantitative way. Although, several quality requirements methods for DSS have been proposed so far, but the research on analyzing quality requirements of DSS are still limited. In this paper, quantitative approach proposed for analyzing ISO / IEC 25010 product quality requirements based on fuzzy logic and likert scale for DSS which aims to quantify quality requirements. Moreover implemented proposed framework on a case study ‘Internet Banking’ and got data from 25 respondents i.e. System Analysts and Domain Experts of banking sector.
Authors and Affiliations
Hasnain Iqbal, Muhammad Babar
Keywords
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- EP ID EP397322
- DOI 10.14569/IJACSA.2016.071232
- Views 72
- Downloads 0
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