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https://doi.org/10.21256/zhaw-30599| Publikationstyp: | Beitrag in wissenschaftlicher Zeitschrift |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | Identifying safety–critical concerns in unmanned aerial vehicle software platforms with SALIENT |
| Autor/-in: | Khatiri, Sajad Di Sorbo, Andrea Zampetti, Fiorella Visaggio, Corrado A. Di Penta, Massimiliano Panichella, Sebastiano |
| et. al: | No |
| DOI: | 10.1016/j.softx.2024.101748 10.21256/zhaw-30599 |
| Erschienen in: | SoftwareX |
| Band(Heft): | 2024 |
| Heft: | 27 |
| Seite(n): | 101748 |
| Erscheinungsdatum: | Mai-2024 |
| Verlag / Hrsg. Institution: | Elsevier |
| ISSN: | 2352-7110 |
| Sprache: | Englisch |
| Schlagwörter: | Unmanned aerial vehicle (UAV); Safety issues; Machine learning (ML); Empirical study |
| Fachgebiet (DDC): | 006: Spezielle Computerverfahren 629: Luftfahrt- und Fahrzeugtechnik |
| Zusammenfassung: | Safety-related concerns may emerge during the operation of unmanned aerial vehicles (UAVs), reported by users and developers in the form of issue reports and pull requests. To help UAV developers identify safety-related concerns, we propose SALIENT, a machine learning (ML)-enabled tool that analyzes individual sentences composing the issue reports and automatically recognizes those describing a safety-related concern. The assessment of the classification performance of the tool on the issues of popular open-source UAV-related projects demonstrate that SALIENT represents a viable solution to assist developers in timely identifying and triaging safety-critical UAV issues, outperforming baselines based on ChatGPT and Google’s Bard. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/30599 |
| Zugehörige Forschungsdaten: | https://github.com/spanichella/SALIENT-TOOL https://doi.org/10.5281/zenodo |
| Volltext Version: | Publizierte Version |
| Lizenz (gemäss Verlagsvertrag): | CC BY 4.0: Namensnennung 4.0 International |
| Departement: | School of Engineering |
| Organisationseinheit: | Institut für Informatik (InIT) |
| Publiziert im Rahmen des ZHAW-Projekts: | COSMOS – DevOps for Complex Cyber-physical Systems of Systems AERIALIST |
| Enthalten in den Sammlungen: | Publikationen School of Engineering |
Dateien zu dieser Ressource:
| Datei | Beschreibung | Größe | Format | |
|---|---|---|---|---|
| 2024_Khatiri-etal_Identifiying-safety-critical-concerns-SALIENT_softx.pdf | 735.21 kB | Adobe PDF |  Öffnen/Anzeigen |
Zur Langanzeige
Khatiri, S., Di Sorbo, A., Zampetti, F., Visaggio, C. A., Di Penta, M., & Panichella, S. (2024). Identifying safety–critical concerns in unmanned aerial vehicle software platforms with SALIENT. SoftwareX, 2024(27), 101748. https://doi.org/10.1016/j.softx.2024.101748
Khatiri, S. et al. (2024) ‘Identifying safety–critical concerns in unmanned aerial vehicle software platforms with SALIENT’, SoftwareX, 2024(27), p. 101748. Available at: https://doi.org/10.1016/j.softx.2024.101748.
S. Khatiri, A. Di Sorbo, F. Zampetti, C. A. Visaggio, M. Di Penta, and S. Panichella, “Identifying safety–critical concerns in unmanned aerial vehicle software platforms with SALIENT,” SoftwareX, vol. 2024, no. 27, p. 101748, May 2024, doi: 10.1016/j.softx.2024.101748.
KHATIRI, Sajad, Andrea DI SORBO, Fiorella ZAMPETTI, Corrado A. VISAGGIO, Massimiliano DI PENTA und Sebastiano PANICHELLA, 2024. Identifying safety–critical concerns in unmanned aerial vehicle software platforms with SALIENT. SoftwareX. Mai 2024. Bd. 2024, Nr. 27, S. 101748. DOI 10.1016/j.softx.2024.101748
Khatiri, Sajad, Andrea Di Sorbo, Fiorella Zampetti, Corrado A. Visaggio, Massimiliano Di Penta, and Sebastiano Panichella. 2024. “Identifying Safety–Critical Concerns in Unmanned Aerial Vehicle Software Platforms with SALIENT.” SoftwareX 2024 (27): 101748. https://doi.org/10.1016/j.softx.2024.101748.
Khatiri, Sajad, et al. “Identifying Safety–Critical Concerns in Unmanned Aerial Vehicle Software Platforms with SALIENT.” SoftwareX, vol. 2024, no. 27, May 2024, p. 101748, https://doi.org/10.1016/j.softx.2024.101748.
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