no code implementations • 14 Nov 2023 • Sergio Moreschini, Ludovik Coba, Valentina Lenarduzzi
Balancing the management of technical debt within recommender systems requires effectively juggling the introduction of new features with the ongoing maintenance and enhancement of the current system.
no code implementations • 23 Mar 2022 • Valentina Golendukhina, Valentina Lenarduzzi, Michael Felderer
Thus, the goal of this study is to investigate the software quality assurance strategies adopted during the development, integration, and maintenance of AI/ML components and code.
no code implementations • Empirical Software Engineering 2022 • Fabiano Pecorelli, Savanna Lujan, Valentina Lenarduzzi, Fabio Palomba, Andrea De Lucia
We conduct a three-step study in which we (1) verify the relation between static analysis warnings and code smells and the potential predictive power of these warnings; (2) build code smell prediction models exploiting and combining the most relevant features coming from the first analysis; (3) compare and combine the performance of the best code smell prediction model with the one achieved by a state of the art approach.
1 code implementation • 12 Nov 2020 • Steffen Herbold, Alexander Trautsch, Benjamin Ledel, Alireza Aghamohammadi, Taher Ahmed Ghaleb, Kuljit Kaur Chahal, Tim Bossenmaier, Bhaveet Nagaria, Philip Makedonski, Matin Nili Ahmadabadi, Kristof Szabados, Helge Spieker, Matej Madeja, Nathaniel Hoy, Valentina Lenarduzzi, Shangwen Wang, Gema Rodríguez-Pérez, Ricardo Colomo-Palacios, Roberto Verdecchia, Paramvir Singh, Yihao Qin, Debasish Chakroborti, Willard Davis, Vijay Walunj, Hongjun Wu, Diego Marcilio, Omar Alam, Abdullah Aldaeej, Idan Amit, Burak Turhan, Simon Eismann, Anna-Katharina Wickert, Ivano Malavolta, Matus Sulir, Fatemeh Fard, Austin Z. Henley, Stratos Kourtzanidis, Eray Tuzun, Christoph Treude, Simin Maleki Shamasbi, Ivan Pashchenko, Marvin Wyrich, James Davis, Alexander Serebrenik, Ella Albrecht, Ethem Utku Aktas, Daniel Strüber, Johannes Erbel
Methods: We use a crowd sourcing approach for manual labeling to validate which changes contribute to bug fixes for each line in bug fixing commits.
Software Engineering
1 code implementation • 7 Oct 2020 • Paul Ralph, Nauman bin Ali, Sebastian Baltes, Domenico Bianculli, Jessica Diaz, Yvonne Dittrich, Neil Ernst, Michael Felderer, Robert Feldt, Antonio Filieri, Breno Bernard Nicolau de França, Carlo Alberto Furia, Greg Gay, Nicolas Gold, Daniel Graziotin, Pinjia He, Rashina Hoda, Natalia Juristo, Barbara Kitchenham, Valentina Lenarduzzi, Jorge Martínez, Jorge Melegati, Daniel Mendez, Tim Menzies, Jefferson Molleri, Dietmar Pfahl, Romain Robbes, Daniel Russo, Nyyti Saarimäki, Federica Sarro, Janet Siegmund, Diomidis Spinellis, Miroslaw Staron, Klaas Stol, Margaret-Anne Storey, Davide Taibi, Damian Tamburri, Marco Torchiano, Christoph Treude, Burak Turhan, XiaoFeng Wang, Sira Vegas
Empirical Standards are natural-language models of a scientific community's expectations for a specific kind of study (e. g. a questionnaire survey).
Software Engineering General Literature