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Publikationstyp: Konferenz: Paper
Art der Begutachtung: Peer review (Publikation)
Titel: An NLP-based tool for software artifacts analysis
Autor/-in: Di Sorbo, Andrea
Visaggio, Corrado A.
Di Penta, Massimiliano
Canfora, Gerardo
Panichella, Sebastiano
et. al: No
DOI: 10.21256/zhaw-23363
Angaben zur Konferenz: 37th International Conference on Software Maintenance and Evolution (ICSME), Luxembourg, 27 September - 1 October 2021
Erscheinungsdatum: 2021
Verlag / Hrsg. Institution: ZHAW Zürcher Hochschule für Angewandte Wissenschaften
Verlag / Hrsg. Institution: Winterthur
Sprache: Englisch
Schlagwörter: Unstructured data mining; Natural language parsing; Software maintenance and evolution
Fachgebiet (DDC): 005: Computerprogrammierung, Programme und Daten
006: Spezielle Computerverfahren
Zusammenfassung: Software developers rely on various repositories and communication channels to exchange relevant information about their ongoing tasks and the status of overall project progress. In this context, semi-structured and unstructured software artifacts have been leveraged by researchers to build recommender systems aimed at supporting developers in different tasks, such as transforming user feedback in maintenance and evolution tasks, suggesting experts, or generating software documentation. More specifically, Natural Language (NL) parsing techniques have been successfully leveraged to automatically identify (or extract) the relevant information embedded in unstructured software artifacts. However, such techniques require the manual identification of patterns to be used for classification purposes. To reduce such a manual effort, we propose an NL parsingbased tool for software artifacts analysis named NEON that can automate the mining of such rules, minimizing the manual effort of developers and researchers. Through a small study involving human subjects with NL processing and parsing expertise, we assess the performance of NEON in identifying rules useful to classify app reviews for software maintenance purposes. Our results show that more than one-third of the rules inferred by NEON are relevant for the proposed task. Demo webpage: https://github.com/adisorbo/NEON tool
URI: https://digitalcollection.zhaw.ch/handle/11475/23363
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
ARIES: Exploiting User Journeys for Supporting Mobility as a Service Platforms
Enthalten in den Sammlungen:Publikationen School of Engineering

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Di Sorbo, A., Visaggio, C. A., Di Penta, M., Canfora, G., & Panichella, S. (2021). An NLP-based tool for software artifacts analysis. 37th International Conference on Software Maintenance and Evolution (ICSME), Luxembourg, 27 September - 1 October 2021. https://doi.org/10.21256/zhaw-23363
Di Sorbo, A. et al. (2021) ‘An NLP-based tool for software artifacts analysis’, in 37th International Conference on Software Maintenance and Evolution (ICSME), Luxembourg, 27 September - 1 October 2021. Winterthur: ZHAW Zürcher Hochschule für Angewandte Wissenschaften. Available at: https://doi.org/10.21256/zhaw-23363.
A. Di Sorbo, C. A. Visaggio, M. Di Penta, G. Canfora, and S. Panichella, “An NLP-based tool for software artifacts analysis,” in 37th International Conference on Software Maintenance and Evolution (ICSME), Luxembourg, 27 September - 1 October 2021, 2021. doi: 10.21256/zhaw-23363.
DI SORBO, Andrea, Corrado A. VISAGGIO, Massimiliano DI PENTA, Gerardo CANFORA und Sebastiano PANICHELLA, 2021. An NLP-based tool for software artifacts analysis. In: 37th International Conference on Software Maintenance and Evolution (ICSME), Luxembourg, 27 September - 1 October 2021. Conference paper. Winterthur: ZHAW Zürcher Hochschule für Angewandte Wissenschaften. 2021
Di Sorbo, Andrea, Corrado A. Visaggio, Massimiliano Di Penta, Gerardo Canfora, and Sebastiano Panichella. 2021. “An NLP-Based Tool for Software Artifacts Analysis.” Conference paper. In 37th International Conference on Software Maintenance and Evolution (ICSME), Luxembourg, 27 September - 1 October 2021. Winterthur: ZHAW Zürcher Hochschule für Angewandte Wissenschaften. https://doi.org/10.21256/zhaw-23363.
Di Sorbo, Andrea, et al. “An NLP-Based Tool for Software Artifacts Analysis.” 37th International Conference on Software Maintenance and Evolution (ICSME), Luxembourg, 27 September - 1 October 2021, ZHAW Zürcher Hochschule für Angewandte Wissenschaften, 2021, https://doi.org/10.21256/zhaw-23363.


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