Data Mining and Machine Learning for Software Engineering
Software engineering is one of the most utilizable research areas for data mining. Developers have attempted to improve software quality by mining and analyzing software data. In any phase of software development life cycle (SDLC), while huge amount of data is produced, some design, security, or sof...
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| Formato: | Capítulo de libro |
| Lenguaje: | inglés |
| Publicado: |
IntechOpen
2020
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| Materias: | |
| Acceso en línea: | https://www.intechopen.com/chapters/71283 |
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| _version_ | 1879164724532215809 |
|---|---|
| author | Kiyak, Elife Ozturk |
| author_browse | Kiyak, Elife Ozturk |
| author_facet | Kiyak, Elife Ozturk |
| author_sort | Kiyak, Elife Ozturk |
| building | IntechOpen |
| collection | Acceso abierto |
| description | Software engineering is one of the most utilizable research areas for data mining. Developers have attempted to improve software quality by mining and analyzing software data. In any phase of software development life cycle (SDLC), while huge amount of data is produced, some design, security, or software problems may occur. In the early phases of software development, analyzing software data helps to handle these problems and lead to more accurate and timely delivery of software projects. Various data mining and machine learning studies have been conducted to deal with software engineering tasks such as defect prediction, effort estimation, etc. This study shows the open issues and presents related solutions and recommendations in software engineering, applying data mining and machine learning techniques. |
| doi_str_mv | 10.5772/intechopen.91448 |
| first_indexed | 2026-10-15T21:38:53Z |
| format | Book Chapter |
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<dc:title>Data Mining and Machine Learning for Software Engineering</dc:title>
<dc:creator>Elife Ozturk Kiyak</dc:creator>
<dc:subject>Physical Sciences, Engineering and Technology</dc:subject>
<dc:description>Software engineering is one of the most utilizable research areas for data mining. Developers have attempted to improve software quality by mining and analyzing software data. In any phase of software development life cycle (SDLC), while huge amount of data is produced, some design, security, or software problems may occur. In the early phases of software development, analyzing software data helps to handle these problems and lead to more accurate and timely delivery of software projects. Various data mining and machine learning studies have been conducted to deal with software engineering tasks such as defect prediction, effort estimation, etc. This study shows the open issues and presents related solutions and recommendations in software engineering, applying data mining and machine learning techniques.</dc:description>
<dc:publisher>IntechOpen</dc:publisher>
<dc:date>2020-03-05</dc:date>
<dc:type>Chapter, Part Of Book</dc:type>
<dc:identifier>https://www.intechopen.com/chapters/71283</dc:identifier>
<dc:identifier>doi:10.5772/intechopen.91448</dc:identifier>
<dc:language>en</dc:language>
<dc:relation>ISBN:978-1-83968-318-3</dc:relation>
<dc:rights>https://creativecommons.org/licenses/by/3.0/</dc:rights>
<dc:source>https://www.intechopen.com/books/9961 ; Data Mining - Methods, Applications and Systems</dc:source>
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| id | intech-71283 |
| institution | IntechOpen |
| isbn | 978-1-83968-318-3 |
| language | English |
| last_indexed | 2026-10-15T21:38:53Z |
| publishDate | 2020 |
| publishDateRange | 2020 |
| publishDateSort | 2020 |
| publisher | IntechOpen |
| publisherStr | IntechOpen |
| record_format | oai_dc |
| spelling | intech-712832020-03-05 Data Mining and Machine Learning for Software Engineering Elife Ozturk Kiyak Physical Sciences, Engineering and Technology Software engineering is one of the most utilizable research areas for data mining. Developers have attempted to improve software quality by mining and analyzing software data. In any phase of software development life cycle (SDLC), while huge amount of data is produced, some design, security, or software problems may occur. In the early phases of software development, analyzing software data helps to handle these problems and lead to more accurate and timely delivery of software projects. Various data mining and machine learning studies have been conducted to deal with software engineering tasks such as defect prediction, effort estimation, etc. This study shows the open issues and presents related solutions and recommendations in software engineering, applying data mining and machine learning techniques. IntechOpen 2020-03-05 Chapter, Part Of Book https://www.intechopen.com/chapters/71283 doi:10.5772/intechopen.91448 en ISBN:978-1-83968-318-3 https://creativecommons.org/licenses/by/3.0/ https://www.intechopen.com/books/9961 ; Data Mining - Methods, Applications and Systems |
| spellingShingle | Physical Sciences, Engineering and Technology Kiyak, Elife Ozturk Data Mining and Machine Learning for Software Engineering |
| title | Data Mining and Machine Learning for Software Engineering |
| title_full | Data Mining and Machine Learning for Software Engineering |
| title_fullStr | Data Mining and Machine Learning for Software Engineering |
| title_full_unstemmed | Data Mining and Machine Learning for Software Engineering |
| title_short | Data Mining and Machine Learning for Software Engineering |
| title_sort | data mining and machine learning for software engineering |
| topic | Physical Sciences, Engineering and Technology |
| url | https://www.intechopen.com/chapters/71283 |
| work_keys_str_mv | AT kiyakelifeozturk dataminingandmachinelearningforsoftwareengineering |