A computational framework for predicting software quality-in-use from software reviews

Software Quality-in-Use (QinU) lies in the eyes of its users. QinU has gained its importance in egovernment, mobile-based, and web applications. Currently, QinU is measured using either ISO standard (e.g. ISO 25010) or customized model approaches. These approaches tend to be incomplete and suffer...

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Main Author:	Atoum, Issa
Format:	Thesis
Language:	English
Published:	2015
Subjects:	T Technology (General)
Online Access:	http://ir.unimas.my/id/eprint/10763/1/Issa%20Atoum%20ft.pdf
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id	my-unimas-ir.10763
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spelling	my-unimas-ir.107632023-03-24T00:34:37Z A computational framework for predicting software quality-in-use from software reviews 2015 Atoum, Issa T Technology (General) Software Quality-in-Use (QinU) lies in the eyes of its users. QinU has gained its importance in egovernment, mobile-based, and web applications. Currently, QinU is measured using either ISO standard (e.g. ISO 25010) or customized model approaches. These approaches tend to be incomplete and suffer from problems of user’s task definition sizing. Therefore, QinU measurement by these approaches has complexity resulting from quantifying QinU systematically. This thesis proposes a computational and novel QinU Framework (QinUF) to measure QinU competently consuming software reviews. The significance of the framework is that it combines the semantic analysis and sentiment analysis research areas. In semantic similarity area, we proposed a novel Weighted Sentence Similarity Measure (WSSM) and developed an algorithm to predict a review-sentence QinU topic (QinU characteristic or software aspect). In the sentiment analysis area, we proposed an algorithm to classify and aggregate software review-sentences into QinU topics. Experiments showed that the QinUF was able to predict software QinU topics on the fly, with high performance compared to selected topic prediction methods. Moreover, results of built use cases showed that employing minimal set of QinU features (properties) enable users to acquire software easily. As for future research, it is recommended to extend QinUF to support additional QinU characteristics, enhance sentiment orientation, specialize the framework to a certain software domain, and implement the framework in a large-scale system. Universiti Malaysia Sarawak, (UNIMAS) 2015 Thesis http://ir.unimas.my/id/eprint/10763/ http://ir.unimas.my/id/eprint/10763/1/Issa%20Atoum%20ft.pdf text en validuser phd doctoral Universiti Malaysia Sarawak Faculty of Computer Science and Information Technology.
institution	Universiti Malaysia Sarawak
collection	UNIMAS Institutional Repository
language	English
topic	T Technology (General)
spellingShingle	T Technology (General) Atoum, Issa A computational framework for predicting software quality-in-use from software reviews
description	Software Quality-in-Use (QinU) lies in the eyes of its users. QinU has gained its importance in egovernment, mobile-based, and web applications. Currently, QinU is measured using either ISO standard (e.g. ISO 25010) or customized model approaches. These approaches tend to be incomplete and suffer from problems of user’s task definition sizing. Therefore, QinU measurement by these approaches has complexity resulting from quantifying QinU systematically. This thesis proposes a computational and novel QinU Framework (QinUF) to measure QinU competently consuming software reviews. The significance of the framework is that it combines the semantic analysis and sentiment analysis research areas. In semantic similarity area, we proposed a novel Weighted Sentence Similarity Measure (WSSM) and developed an algorithm to predict a review-sentence QinU topic (QinU characteristic or software aspect). In the sentiment analysis area, we proposed an algorithm to classify and aggregate software review-sentences into QinU topics. Experiments showed that the QinUF was able to predict software QinU topics on the fly, with high performance compared to selected topic prediction methods. Moreover, results of built use cases showed that employing minimal set of QinU features (properties) enable users to acquire software easily. As for future research, it is recommended to extend QinUF to support additional QinU characteristics, enhance sentiment orientation, specialize the framework to a certain software domain, and implement the framework in a large-scale system.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Atoum, Issa
author_facet	Atoum, Issa
author_sort	Atoum, Issa
title	A computational framework for predicting software quality-in-use from software reviews
title_short	A computational framework for predicting software quality-in-use from software reviews
title_full	A computational framework for predicting software quality-in-use from software reviews
title_fullStr	A computational framework for predicting software quality-in-use from software reviews
title_full_unstemmed	A computational framework for predicting software quality-in-use from software reviews
title_sort	computational framework for predicting software quality-in-use from software reviews
granting_institution	Universiti Malaysia Sarawak
granting_department	Faculty of Computer Science and Information Technology.
publishDate	2015
url	http://ir.unimas.my/id/eprint/10763/1/Issa%20Atoum%20ft.pdf
_version_	1783728071254212608

A computational framework for predicting software quality-in-use from software reviews

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