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https://doi.org/10.21256/zhaw-25771| Publikationstyp: | Konferenz: Paper |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | NLBSE’22 tool competition |
| Autor/-in: | Kallis, Rafael Chaparro, Oscar Di Sorbo, Andrea Panichella, Sebastiano |
| et. al: | No |
| DOI: | 10.1145/3528588.3528664 10.21256/zhaw-25771 |
| Tagungsband: | 2022 IEEE/ACM 1st International Workshop on Natural Language-Based Software Engineering (NLBSE) |
| Seite(n): | 25 |
| Seiten bis: | 28 |
| Angaben zur Konferenz: | 1st International Workshop on Natural Language-Based Software Engineering (NLBSE), Pittsburgh, USA (online), 8 May 2022 |
| Erscheinungsdatum: | 2022 |
| Verlag / Hrsg. Institution: | IEEE |
| ISBN: | 978-1-4503-9343-0 |
| Sprache: | Englisch |
| Fachgebiet (DDC): | 006: Spezielle Computerverfahren |
| Zusammenfassung: | We report on the organization and results of the first edition of the Tool Competition from the International Workshop on Natural Language-based Software Engineering (NLBSE’22). This year, five teams submitted multiple classification models to automatically classify issue reports as bugs, enhancements, or questions. Most of them are based on BERT (Bidirectional Encoder Representations from Transformers) and were fine-tuned and evaluated on a benchmark dataset of 800k issue reports. The goal of the competition was to improve the classification performance of a baseline model based on fastText. This report provides details of the competition, including its rules, the teams and contestant models, and the ranking of models based on their average classification performance across the issue types. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/25771 |
| Volltext Version: | Akzeptierte Version |
| Lizenz (gemäss Verlagsvertrag): | Lizenz gemäss Verlagsvertrag |
| Departement: | School of Engineering |
| Organisationseinheit: | Institut für Informatik (InIT) |
| Publiziert im Rahmen des ZHAW-Projekts: | COSMOS – DevOps for Complex Cyber-physical Systems of Systems |
| Enthalten in den Sammlungen: | Publikationen School of Engineering |
Dateien zu dieser Ressource:
| Datei | Beschreibung | Größe | Format | |
|---|---|---|---|---|
| 2022_Kallis-etal_NLBSE22-Tool-Competition.pdf | Accepted Version | 123.23 kB | Adobe PDF |  Öffnen/Anzeigen |
Zur Langanzeige
Kallis, R., Chaparro, O., Di Sorbo, A., & Panichella, S. (2022). NLBSE’22 tool competition [Conference paper]. 2022 IEEE/ACM 1st International Workshop on Natural Language-Based Software Engineering (NLBSE), 25–28. https://doi.org/10.1145/3528588.3528664
Kallis, R. et al. (2022) ‘NLBSE’22 tool competition’, in 2022 IEEE/ACM 1st International Workshop on Natural Language-Based Software Engineering (NLBSE). IEEE, pp. 25–28. Available at: https://doi.org/10.1145/3528588.3528664.
R. Kallis, O. Chaparro, A. Di Sorbo, and S. Panichella, “NLBSE’22 tool competition,” in 2022 IEEE/ACM 1st International Workshop on Natural Language-Based Software Engineering (NLBSE), 2022, pp. 25–28. doi: 10.1145/3528588.3528664.
KALLIS, Rafael, Oscar CHAPARRO, Andrea DI SORBO und Sebastiano PANICHELLA, 2022. NLBSE’22 tool competition. In: 2022 IEEE/ACM 1st International Workshop on Natural Language-Based Software Engineering (NLBSE). Conference paper. IEEE. 2022. S. 25–28. ISBN 978-1-4503-9343-0
Kallis, Rafael, Oscar Chaparro, Andrea Di Sorbo, and Sebastiano Panichella. 2022. “NLBSE’22 Tool Competition.” Conference paper. In 2022 IEEE/ACM 1st International Workshop on Natural Language-Based Software Engineering (NLBSE), 25–28. IEEE. https://doi.org/10.1145/3528588.3528664.
Kallis, Rafael, et al. “NLBSE’22 Tool Competition.” 2022 IEEE/ACM 1st International Workshop on Natural Language-Based Software Engineering (NLBSE), IEEE, 2022, pp. 25–28, https://doi.org/10.1145/3528588.3528664.
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