Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Palomba, F. (Fabio)"'
Autor:
Lomio, F. (Francesco), Pascarella, L. (Luca), Palomba, F. (Fabio), Lenarduzzi, V. (Valentina)
Publikováno v:
2022 48th Euromicro Conference on Software Engineering and Advanced Applications (SEAA).
Fine-grained just-in-time defect prediction aims at identifying likely defective files within new commits. Popular techniques are based on supervised learning, where machine learning algorithms are fed with historical data. One of the limitations of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bd2de11629566164d37a6c609731a35e
https://doi.org/10.1109/seaa56994.2022.00049
https://doi.org/10.1109/seaa56994.2022.00049
Autor:
Lomio, F. (Francesco), Iannone, E. (Emanuele), De Lucia, A. (Andrea), Palomba, F. (Fabio), Lenarduzzi, V. (Valentina)
Background: Software vulnerabilities are weaknesses in source code that might be exploited to cause harm or loss. Previous work has proposed a number of automated machine learning approaches to detect them. Most of these techniques work at release-le
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2423::6790b9b5dda418d976bb40b49a2aec56
http://urn.fi/urn:nbn:fi-fe2022051134386
http://urn.fi/urn:nbn:fi-fe2022051134386
Autor:
Lenarduzzi, V. (Valentina), Pecorelli, F. (Fabiano), Saarimaki, N. (Nyyti), Lujan, S. (Savanna), Palomba, F. (Fabio)
Publikováno v:
SSRN Electronic Journal.
Background: Developers use Static Analysis Tools (SATs) to control for potential quality issues in source code, including defects and technical debt. Tool vendors have devised quite a number of tools, which makes it harder for practitioners to select
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0187976ad9ff46e9f0845f30f5a86471
https://doi.org/10.2139/ssrn.4044439
https://doi.org/10.2139/ssrn.4044439