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
Network-State-Aware Quality of Service Provisioning for the Internet of Things
The Internet of Things (IoT) describes a diverse range of technologies to enable a diverse range of applications using diverse platforms for communication. IP-enabled Wireless Sensor Networks (6LoWPAN) are an integral pa...
A Comparative study of Arabic handwritten characters invariant feature
this paper is practically interested in the unchangeable feature of Arabic handwritten character. It presents results of comparative study achieved on certain features extraction techniques of handwritten cha...
Fir Filter Design Using The Signed-Digit Number System and Carry Save Adders – A Comparison
This work looks at optimizing finite impulse response (FIR) filters from an arithmetic perspective. Since the main two arithmetic operations in the convolution equations are addition and multiplication, they are the targ...
Feature Weight Optimization Mechanism for Email Spam Detection based on Two-step Clustering Algorithm and Logistic Regression Method
This research proposed an improved filtering spam technique for suspected emails, messages based on feature weight and the combination of two-step clustering and logistic regression algorithm. Unique, important features...
Distance Prediction for Commercial Serial Crime Cases Using Time Delay Neural Networks
The prediction of the next serial criminal time is important in the field of criminology for preventing the recurring actions of serial criminals. In the associated dynamic systems, one of the main sources of instability...