| | SLO | ENG | Cookies and privacy

Bigger font | Smaller font

Show document Help

Title:Primerjava generativnih modelov umetne inteligence za generiranje programske kode : magistrsko delo
Authors:ID Ključevšek, Jan (Author)
ID Verber, Domen (Mentor) More about this mentor... New window
Files:.pdf MAG_Kljucevsek_Jan_2025.pdf (1,94 MB)
MD5: AF3DDA4902935E23749BEC677BB630EE
 
.zip MAG_Kljucevsek_Jan_2025.zip (6,58 MB)
MD5: 40EF3984FBF3C57ED5C285021CAD523A
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:Cilj magistrskega dela je bil primerjalno oceniti kakovost programske kode, ki jo generirajo modeli umetne inteligence ChatGPT (4o, o1), Gemini (Flash, Pro) in Microsoft Copilot. Na področju generativne umetne inteligence in kakovosti programske opreme smo z uporabo kvantitativnih metrik in orodij analizirali kodo, generirano za različno zahtevne naloge. Rezultati kažejo, da vsi modeli ustvarjajo sintaktično pravilno kodo, a se razlikujejo predvsem v funkcionalni pravilnosti, kompleksnosti in berljivosti. Plačljivi modeli so bili pravilnejši, a kompleksnejši; brezplačni (Copilot, Gemini Flash) pa enostavnejši in berljivejši. Priporočamo izbiro modela glede na prioritete projekta.
Keywords:generativna umetna inteligenca, generiranje programske kode, kakovost programske kode, metrike kakovosti kode
Publication status:Published
Publication version:Version of Record
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[J. Ključevšek]
Year of publishing:2025
Number of pages:1 spletni vir (1 datoteka PDF (XIII, 82 str.))
PID:20.500.12556/DKUM-92843 New window
UDC:004.8:004.4'415(043.2)
COBISS.SI-ID:239013891 New window
Publication date in DKUM:06.06.2025
Views:225
Downloads:73
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
:
Copy citation
  
Average score:(0 votes)
Your score:Voting is allowed only for logged in users.
Share:Bookmark and Share



Hover the mouse pointer over a document title to show the abstract or click on the title to get all document metadata.

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:18.05.2025

Secondary language

Language:English
Title:Comparison of generative artificial intelligence models for code generation
Abstract:The objective of the master's thesis was to comparatively evaluate the quality of program code generated by the artificial intelligence models ChatGPT (4o, o1), Gemini (Flash, Pro), and Microsoft Copilot. In the field of generative artificial intelligence and software quality, we analyzed code generated for tasks of varying complexity using quantitative metrics and tools. The results show that all models produce syntactically correct code, but differ primarily in functional correctness, complexity, and readability. Paid models were more correct but more complex; free models (Copilot, Gemini Flash) were simpler and more readable. We recommend selecting a model based on project priorities.
Keywords:generative artificial intelligence, code generation, code quality, code quality metrics


Comments

Leave comment

You must log in to leave a comment.

Comments (0)
0 - 0 / 0
 
There are no comments!

Back
Logos of partners University of Maribor University of Ljubljana University of Primorska University of Nova Gorica