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Title:Identifikacija slabe kode s strojnim učenjem
Authors:ID Šoln, Roman (Author)
ID Kokol, Peter (Mentor) More about this mentor... New window
Files:.pdf VS_Soln_Roman_2019.pdf (1,56 MB)
MD5: 94A5310EAE3EDD28FA01494FE514E36F
PID: 20.500.12556/dkum/227de1f4-bee4-4274-a85b-f6197adf2c5b
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:Diplomsko delo opisuje nastanek in razvoj aplikacije za identifikacijo slabe kode s strojnim učenjem. Predstavljen je začetek, kdaj se je vse skupaj začelo razvijati, ter že obstoječe rešitve. Predstavljeni so vonji, ki jih lahko koda oddaja ter tudi, kako te vonje odstranimo. Opisano je tudi, kdaj vonje ignoriramo ter zakaj to storimo. Na kratko so opisane uporabljene tehnologije ter orodja in njihove glavne značilnosti. Opisan je potek razvoja same aplikacije po delih, ki so ključnega pomena za pravilno delovanje same aplikacije. Predstavljen je tudi videz in delovanje same aplikacije.
Keywords:Strojno učenje, priprava podatkov, identifikacija, slaba koda
Place of publishing:[Maribor
Publisher:R. Šoln
Year of publishing:2019
PID:20.500.12556/DKUM-73178 New window
UDC:004.85:004.056.5(043.2)
COBISS.SI-ID:22212118 New window
NUK URN:URN:SI:UM:DK:N28NF9AY
Publication date in DKUM:19.03.2019
Views:2057
Downloads:202
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
:
ŠOLN, Roman, 2019, Identifikacija slabe kode s strojnim učenjem [online]. Bachelor’s thesis. Maribor : R. Šoln. [Accessed 26 March 2025]. Retrieved from: https://dk.um.si/IzpisGradiva.php?lang=eng&id=73178
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:27.02.2019

Secondary language

Language:English
Title:Bad code identification with machine learning
Abstract:The diploma work describes the creation and development of an application for the identification of a bad code with machine learning. Represent the beginning, when all began to develop and describe already existing solutions. Represents the smells and why code can stink bad and how to remuve it. It is also described when we should ignore the smells, and why we should do it. Describes the technologies and tools used and their main characteristics. The development of the application itself is divided into sections that are crucial for the proper functioning of the application itself. The appearance and performance of the application itself is presented.
Keywords:Machine learning, data preparation, identification, bad code


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