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18: Aprendizado de Máquina em Engenharia de Software, com Maurício Aniche (TU Delft)

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Content provided by Fronteiras da Engenharia de Software. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Fronteiras da Engenharia de Software or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Neste episódio, conversamos com Maurício F. Aniche, professor na Universidade Tecnológica de Delft (TU Delft). O tema foi Aprendizado de Máquina em Engenharia de Software. A página do Maurício é https://www.mauricioaniche.com/. Ele está no Twitter como @mauricioaniche. Artigos mencionados: Jeroen Castelein, Maurício Finavaro Aniche, Mozhan Soltani, Annibale Panichella, Arie van Deursen: Search-based test data generation for SQL queries. ICSE 2018. Ludewig, M., Mauro, N., Latifi, S. and Jannach, D.: "Performance Comparison of Neural and Non-Neural Approaches to Session-based Recommendation". In: Proceedings of the 2019 ACM Conference on Recommender Systems (RecSys 2019). Copenhagen, 2019 Henk Grent, Aleksei Akimov, Maurício Aniche: Automatically Identifying Parameter Constraints in Complex Web APIs: A Case Study at Adyen. ICSE (SEIP) 2021. Casper Schröder, Adriaan van der Feltz, Annibale Panichella, Maurício Aniche: Search-Based Software Re-Modularization: A Case Study at Adyen. ICSE (SEIP) 2021. Jeanderson Cândido, Jan Haesen, Maurício Aniche, Arie van Deursen: An Exploratory Study of Log Placement Recommendation in an Enterprise System. MSR 2021: 143-154 Bart van Oort, Luis Cruz, Maurício Aniche, Arie van Deursen: The Prevalence of Code Smells in Machine Learning projects. WAIN@ICSE 2021 Mauricio Finavaro Aniche, Gabriele Bavota, Christoph Treude, Marco Aurélio Gerosa, Arie van Deursen: Code smells for Model-View-Controller architectures. Empir. Softw. Eng. 23(4): 2121-2157 (2018) Maurício Aniche, Frank Mulder, Felienne Hermans: Grading 600+ Students: A Case Study on Peer and Self Grading. ICSE (SEET) 2021: 211-220 Nossa equipe é formada por: Leonardo Fernandes (IFAL) Gustavo Pinto (UFPA) Fabio Petrillo (UQAC) Danilo Monteiro (Zup Innovation) Adolfo Gustavo Serra Seca Neto (UTFPR) - co-host deste episódio Ingrid Nunes (UFRGS) - co-host deste episódio Nosso site é https://fronteirases.github.io/. A edição deste episódio foi feita pela Zup Innovation. --- Send in a voice message: https://podcasters.spotify.com/pod/show/fronteirases/message
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54 episodes

Artwork
iconShare
 
Manage episode 307376257 series 2931673
Content provided by Fronteiras da Engenharia de Software. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Fronteiras da Engenharia de Software or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Neste episódio, conversamos com Maurício F. Aniche, professor na Universidade Tecnológica de Delft (TU Delft). O tema foi Aprendizado de Máquina em Engenharia de Software. A página do Maurício é https://www.mauricioaniche.com/. Ele está no Twitter como @mauricioaniche. Artigos mencionados: Jeroen Castelein, Maurício Finavaro Aniche, Mozhan Soltani, Annibale Panichella, Arie van Deursen: Search-based test data generation for SQL queries. ICSE 2018. Ludewig, M., Mauro, N., Latifi, S. and Jannach, D.: "Performance Comparison of Neural and Non-Neural Approaches to Session-based Recommendation". In: Proceedings of the 2019 ACM Conference on Recommender Systems (RecSys 2019). Copenhagen, 2019 Henk Grent, Aleksei Akimov, Maurício Aniche: Automatically Identifying Parameter Constraints in Complex Web APIs: A Case Study at Adyen. ICSE (SEIP) 2021. Casper Schröder, Adriaan van der Feltz, Annibale Panichella, Maurício Aniche: Search-Based Software Re-Modularization: A Case Study at Adyen. ICSE (SEIP) 2021. Jeanderson Cândido, Jan Haesen, Maurício Aniche, Arie van Deursen: An Exploratory Study of Log Placement Recommendation in an Enterprise System. MSR 2021: 143-154 Bart van Oort, Luis Cruz, Maurício Aniche, Arie van Deursen: The Prevalence of Code Smells in Machine Learning projects. WAIN@ICSE 2021 Mauricio Finavaro Aniche, Gabriele Bavota, Christoph Treude, Marco Aurélio Gerosa, Arie van Deursen: Code smells for Model-View-Controller architectures. Empir. Softw. Eng. 23(4): 2121-2157 (2018) Maurício Aniche, Frank Mulder, Felienne Hermans: Grading 600+ Students: A Case Study on Peer and Self Grading. ICSE (SEET) 2021: 211-220 Nossa equipe é formada por: Leonardo Fernandes (IFAL) Gustavo Pinto (UFPA) Fabio Petrillo (UQAC) Danilo Monteiro (Zup Innovation) Adolfo Gustavo Serra Seca Neto (UTFPR) - co-host deste episódio Ingrid Nunes (UFRGS) - co-host deste episódio Nosso site é https://fronteirases.github.io/. A edição deste episódio foi feita pela Zup Innovation. --- Send in a voice message: https://podcasters.spotify.com/pod/show/fronteirases/message
  continue reading

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