Crowdsource requirements engineering: Using online reviews as input to software features clustering
As to date, various software being produced to help in our daily routines. At times, there are complaints on errors or faults lodged by users over the internet. This information can be valuable for software development teams to enhance the software functionalities in the next releases. Not only...
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Faculty of Electronic and Computer Engineering, Universiti Teknikal Malaysia Melaka
2017
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Online Access: | http://irep.iium.edu.my/62949/1/62949%20Crowdsource%20requirements%20engineering.pdf http://irep.iium.edu.my/62949/2/62949%20Crowdsource%20requirements%20engineering%20SCOPUS.pdf http://irep.iium.edu.my/62949/ http://journal.utem.edu.my/index.php/jtec/article/view/2891/2025 |
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my.iium.irep.62949 http://irep.iium.edu.my/62949/ Crowdsource requirements engineering: Using online reviews as input to software features clustering Bakar, Noor Hasrina M. Kasirun, Zarinah Salleh, Norsaremah Halim, Azni H. T Technology (General) As to date, various software being produced to help in our daily routines. At times, there are complaints on errors or faults lodged by users over the internet. This information can be valuable for software development teams to enhance the software functionalities in the next releases. Not only that, these comments contain important software features that can be extracted and reuse for future development of similar software systems. Reviews provided by various user from unknown background is an example of open call involvement in crowdsource software engineering. In this paper, sample software reviews available in the internet were collected. In the experiment conducted, twenty-five groups of random software reviews within the domain of children online learning software were selected as input to crowdsource requirements engineering. T h e extracted reviews were then clustered into related groups by using K-Means algorithm. The clustering results achieved by K-Means were evaluated in terms of cluster compactness and cohesion. A statistically significant result with time efficiency obtained and reported at the end of this paper. Based on this information, this paper provides some recommendations on how user reviews can be used as input to the crowdsource requirements engineering either for improving existing software or for production of a new similar system Faculty of Electronic and Computer Engineering, Universiti Teknikal Malaysia Melaka 2017 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/62949/1/62949%20Crowdsource%20requirements%20engineering.pdf application/pdf en http://irep.iium.edu.my/62949/2/62949%20Crowdsource%20requirements%20engineering%20SCOPUS.pdf Bakar, Noor Hasrina and M. Kasirun, Zarinah and Salleh, Norsaremah and Halim, Azni H. (2017) Crowdsource requirements engineering: Using online reviews as input to software features clustering. In: 10th Malaysian Software Engineering Conference (MySEC 2017), 7th-9th August 2017, Terengganu, Malaysia. http://journal.utem.edu.my/index.php/jtec/article/view/2891/2025 |
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T Technology (General) Bakar, Noor Hasrina M. Kasirun, Zarinah Salleh, Norsaremah Halim, Azni H. Crowdsource requirements engineering: Using online reviews as input to software features clustering |
description |
As to date, various software being produced to help
in our daily routines. At times, there are complaints on errors or
faults lodged by users over the internet. This information can be
valuable for software development teams to enhance the
software functionalities in the next releases. Not only that, these
comments contain important software features that can be
extracted and reuse for future development of similar software
systems. Reviews provided by various user from unknown
background is an example of open call involvement in
crowdsource software engineering. In this paper, sample
software reviews available in the internet were collected. In the
experiment conducted, twenty-five groups of random
software reviews within the domain of children online
learning software were selected as input to crowdsource
requirements engineering. T h e extracted reviews were then
clustered into related groups by using K-Means algorithm.
The clustering results achieved by K-Means were evaluated in
terms of cluster compactness and cohesion. A statistically
significant result with time efficiency obtained and reported
at the end of this paper. Based on this information, this paper
provides some recommendations on how user reviews can be
used as input to the crowdsource requirements engineering
either for improving existing software or for production of a new
similar system |
format |
Conference or Workshop Item |
author |
Bakar, Noor Hasrina M. Kasirun, Zarinah Salleh, Norsaremah Halim, Azni H. |
author_facet |
Bakar, Noor Hasrina M. Kasirun, Zarinah Salleh, Norsaremah Halim, Azni H. |
author_sort |
Bakar, Noor Hasrina |
title |
Crowdsource requirements engineering: Using online reviews as input to software features clustering |
title_short |
Crowdsource requirements engineering: Using online reviews as input to software features clustering |
title_full |
Crowdsource requirements engineering: Using online reviews as input to software features clustering |
title_fullStr |
Crowdsource requirements engineering: Using online reviews as input to software features clustering |
title_full_unstemmed |
Crowdsource requirements engineering: Using online reviews as input to software features clustering |
title_sort |
crowdsource requirements engineering: using online reviews as input to software features clustering |
publisher |
Faculty of Electronic and Computer Engineering, Universiti Teknikal Malaysia Melaka |
publishDate |
2017 |
url |
http://irep.iium.edu.my/62949/1/62949%20Crowdsource%20requirements%20engineering.pdf http://irep.iium.edu.my/62949/2/62949%20Crowdsource%20requirements%20engineering%20SCOPUS.pdf http://irep.iium.edu.my/62949/ http://journal.utem.edu.my/index.php/jtec/article/view/2891/2025 |
_version_ |
1643617105409474560 |
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13.214268 |