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dc.contributor.author
Vasileiou, Maria
en
dc.date.accessioned
2023-06-09T11:23:44Z
dc.date.available
2023-06-09T11:23:44Z
dc.date.issued
2023-06-09
dc.identifier.uri
https://repository.ihu.edu.gr//xmlui/handle/11544/30287
dc.rights
Default License
dc.subject
Data mining
en
dc.subject
Software managemen
el
dc.title
Data mining software management
en
heal.type
masterThesis
en_US
heal.creatorID.email
mvasileiou@ihu.edu.gr
heal.dateAvailable
2023-03-13
heal.language
en
en_US
heal.access
free
en_US
heal.license
http://creativecommons.org/licenses/by-nc/4.0
en_US
heal.recordProvider
School of Science and Technology, MSc in Data Science
en_US
heal.publicationDate
2023-03-13
heal.abstract
With the continuous technological evolution, the amount of software that is implemented is constantly increasing. Also, due to the fact that electronic devices are nowadays a significant part of people’s lives, there is a need for the software to become increasingly better. As the demand grows so does the need to produce new software and improve the existing one. In order to achieve the upgrade of the existing software as quickly as possible while remaining on budget, in this dissertation, a number of data mining techniques were used. Many techniques have been used in previous research for software defect detection. In this dissertation, some of those techniques were applied in data extracted from the source code of notepad++ to find bugs and defects. Finally, the results of these techniques will be validated using the actual changes that have been made in the next release of the chosen application and the purpose is to examine and compare the results of the algorithms that were used.
el
heal.advisorName
Tjortjis, Christos
el
heal.committeeMemberName
Berberidis
en
heal.committeeMemberName
Koukaras
en
heal.academicPublisher
IHU
el
heal.academicPublisherID
ihu
en_US


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