Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Jelena Slivka"'
Publikováno v:
Machine Learning with Applications, Vol 16, Iss , Pp 100557- (2024)
Large language models like ChatGPT can learn in-context (ICL) from examples. Studies showed that, due to ICL, ChatGPT achieves impressive performance in various natural language processing tasks. However, to the best of our knowledge, this is the fir
Externí odkaz:
https://doaj.org/article/ebc73ccee1044080a7e226f77b501ce2
A code smell is a surface indication that usually corresponds to a deeper problem in the system. Detecting and removing code smells is crucial for sustainable software development. However, manual detection can be daunting and time-consuming. Machine
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5ab5d7cc8df172598306b83e6c95cfe1
https://doi.org/10.36227/techrxiv.21732059.v1
https://doi.org/10.36227/techrxiv.21732059.v1
Publikováno v:
2022 IEEE 20th Jubilee International Symposium on Intelligent Systems and Informatics (SISY).
Publikováno v:
Computer Applications in Engineering Education
The coronavirus disease of 2019 (COVID‐19) pandemic has severely crippled our globalized society. Despite the chaos, much of our civilization continued to function, thanks to contemporary information and communication technologies. In education, th
Autor:
Goran Sladić, Dragan Vidaković, Katarina-Glorija Grujić, Simona Prokić, Jelena Slivka, Nikola Luburić, Aleksandar Kovačević
Code smells are code structures that harm the software’s quality. An obstacle to developing automatic detectors is the available datasets' limitations. Furthermore, researchers developed many solutions for Java while neglecting other programming la
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bbd2d85e167c61bc959ff482fc4de2e6
https://doi.org/10.36227/techrxiv.19682754.v1
https://doi.org/10.36227/techrxiv.19682754.v1
Autor:
Nikola Luburić, Luka Dorić, Jelena Slivka, Dragan Vidaković, Katarina-Glorija Grujić, Aleksandar Kovačević, Simona Prokić
Publikováno v:
SSRN Electronic Journal.
Autor:
Nikola Luburić, Dragan Vidaković, Jelena Slivka, Simona Prokić, Katarina-Glorija Grujić, Aleksandar Kovačević, Goran Sladić
Publikováno v:
Proceedings of the 14th International Conference on Computer Supported Education.
Autor:
Katarina-Glorija Grujić, Simona Prokić, Aleksandar Kovačević, Nikola Luburić, Dragan Vidaković, Jelena Slivka
Publikováno v:
SSRN Electronic Journal.
Autor:
Goran Sladić, Simona Prokić, Nikola Luburić, Katarina-Glorija Grujić, Dragan Vidaković, Jelena Slivka, Aleksandar Kovačević
Code smells are structures in code that often have a negative impact on its quality. Manually detecting code smells is challenging and researchers proposed many automatic code smell detectors. Most of the studies propose detectors based on code metri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::50397eb657654105d751ae313033792e
https://doi.org/10.36227/techrxiv.17206010.v1
https://doi.org/10.36227/techrxiv.17206010.v1
Autor:
Dragan Vidaković, Aleksandar Kovačević, Goran Sladić, Nikola Luburić, Simona Prokic, Jelena Slivka, Katarina-Glorija Grujić
Publikováno v:
MIPRO
Many different code snippets can implement the same software feature. However, a significant subset of these possible solutions contains difficult-to-understand code that harms the software's maintainability and evolution. Such low-quality code snipp