ASSRES, Gebremariam, BHANDARI, Guru, SHALAGINOV, Andrii, GRONLI, Tor-Morten und GHINEA, Gheorghita, 2025. State-of-the-Art and Challenges of Engineering ML- Enabled Software Systems in the Deep Learning Era. ACM Computing Surveys. 1 Oktober 2025. Vol. 57, no. 10, p. 1-35. DOI 10.1145/3731597.
Elsevier - Harvard (with titles)Assres, G., Bhandari, G., Shalaginov, A., Gronli, T.-M., Ghinea, G., 2025. State-of-the-Art and Challenges of Engineering ML- Enabled Software Systems in the Deep Learning Era. ACM Computing Surveys 57, 1-35. https://doi.org/10.1145/3731597
American Psychological Association 7th editionAssres, G., Bhandari, G., Shalaginov, A., Gronli, T.-M., & Ghinea, G. (2025). State-of-the-Art and Challenges of Engineering ML- Enabled Software Systems in the Deep Learning Era. ACM Computing Surveys, 57(10), 1-35. https://doi.org/10.1145/3731597
Springer - Basic (author-date)Assres G, Bhandari G, Shalaginov A, Gronli T-M, Ghinea G (2025) State-of-the-Art and Challenges of Engineering ML- Enabled Software Systems in the Deep Learning Era.. ACM Computing Surveys 57:1-35. https://doi.org/10.1145/3731597
Juristische Zitierweise (Stüber) (Deutsch)Assres, Gebremariam/ Bhandari, Guru/ Shalaginov, Andrii/ Gronli, Tor-Morten/ Ghinea, Gheorghita, State-of-the-Art and Challenges of Engineering ML- Enabled Software Systems in the Deep Learning Era., ACM Computing Surveys 2025, 1-35.