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Investigation of software maintainability prediction models

Software must be well developed and maintainable to adapt to the constantly changing requirement of the competitive world. In this article, we distinct different software maintainability prediction models and techniques which can help us to predict the maintainability of software, and can lead us to...

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Bibliographic Details
Main Authors: Shafiabady, A., Mahrin, M. N., Samadi, M.
Format: Conference or Workshop Item
Published: Institute of Electrical and Electronics Engineers Inc. 2016
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://eprints.utm.my/id/eprint/73371/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84962784432&doi=10.1109%2fICACT.2016.7423558&partnerID=40&md5=a5ebc2e38c1fcf3d08d297b1617b84fb
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id my.utm.73371
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spelling my.utm.733712017-11-21T03:28:08Z http://eprints.utm.my/id/eprint/73371/ Investigation of software maintainability prediction models Shafiabady, A. Mahrin, M. N. Samadi, M. QA75 Electronic computers. Computer science Software must be well developed and maintainable to adapt to the constantly changing requirement of the competitive world. In this article, we distinct different software maintainability prediction models and techniques which can help us to predict the maintainability of software, and can lead us to minimum the effort required to fix the faults in the software and the software will be more maintainable. We have gathered our data from different studies focused on the accuracy of the prediction models as criteria. The results of our study showed that there is a little evidence on the accuracy results of the software maintainability prediction models. Institute of Electrical and Electronics Engineers Inc. 2016 Conference or Workshop Item PeerReviewed Shafiabady, A. and Mahrin, M. N. and Samadi, M. (2016) Investigation of software maintainability prediction models. In: 18th International Conference on Advanced Communications Technology, ICACT 2016, 31 Jan - 3 Feb 2016, South Korea. https://www.scopus.com/inward/record.uri?eid=2-s2.0-84962784432&doi=10.1109%2fICACT.2016.7423558&partnerID=40&md5=a5ebc2e38c1fcf3d08d297b1617b84fb
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Shafiabady, A.
Mahrin, M. N.
Samadi, M.
Investigation of software maintainability prediction models
description Software must be well developed and maintainable to adapt to the constantly changing requirement of the competitive world. In this article, we distinct different software maintainability prediction models and techniques which can help us to predict the maintainability of software, and can lead us to minimum the effort required to fix the faults in the software and the software will be more maintainable. We have gathered our data from different studies focused on the accuracy of the prediction models as criteria. The results of our study showed that there is a little evidence on the accuracy results of the software maintainability prediction models.
format Conference or Workshop Item
author Shafiabady, A.
Mahrin, M. N.
Samadi, M.
author_facet Shafiabady, A.
Mahrin, M. N.
Samadi, M.
author_sort Shafiabady, A.
title Investigation of software maintainability prediction models
title_short Investigation of software maintainability prediction models
title_full Investigation of software maintainability prediction models
title_fullStr Investigation of software maintainability prediction models
title_full_unstemmed Investigation of software maintainability prediction models
title_sort investigation of software maintainability prediction models
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2016
url http://eprints.utm.my/id/eprint/73371/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84962784432&doi=10.1109%2fICACT.2016.7423558&partnerID=40&md5=a5ebc2e38c1fcf3d08d297b1617b84fb
_version_ 1643656644253450240
score 13.211869

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