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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| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
Faculty of Electronic and Computer Engineering, Universiti Teknikal Malaysia Melaka
2017
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| Subjects: | |
| 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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| Summary: | 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 |
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