Towards Resolving Software Quality-in-Use Measurement Challenges

Software quality-in-use comprehends the quality from user’s perspectives. It has gained its importance in e-learning applications, mobile service based applications and project management tools. User’s decisions on software acquisitions are often ad hoc or based on preference due to difficulty in...

Full description

Saved in:
Bibliographic Details
Main Authors: Issa, Atoum, Bong, Chih How, Narayanan, Kulathuramaiyer
Format: Article
Language:English
Published: Computing and Information Sciences 2014
Subjects:
Online Access:http://ir.unimas.my/id/eprint/8455/1/Towards%20Resolving%20Software%20Quality-in-Use%20Measurement%20Challenges%20%28abstract%29.pdf
http://ir.unimas.my/id/eprint/8455/
http://www.researchgate.net/publication/269703437_Towards_Resolving_Software_Quality-in-Use_Measurement_Challenges
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Software quality-in-use comprehends the quality from user’s perspectives. It has gained its importance in e-learning applications, mobile service based applications and project management tools. User’s decisions on software acquisitions are often ad hoc or based on preference due to difficulty in quantitatively measure software quality-in-use. However, why qualityin- use measurement is difficult? Although there are many software quality models to our knowledge, no works surveys the challenges related to software quality-in-use measurement. This paper has two main contributions; 1) presents major issues and challenges in measuring software quality-in-use in the context of the ISO SQuaRE series and related software quality models, 2) Presents a novel framework that can be used to predict software quality-in-use, and 3) presents preliminary results of quality-in-use topic prediction. Concisely, the issues are related to the complexity of the current standard models and the limitations and incompleteness of the customized software quality models. The proposed framework employs sentiment analysis techniques to predict software quality-in-use.