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El Baff, Roxanne und Santhanam, Sivasurya und Hecking, Tobias (2021) Quantifying Synergy between Software Projects using README Files Only. In: 33rd International Conference on Software Engineering and Knowledge Engineering, SEKE 2021, 33. KSI Research Inc. and Knowledge Systems Institute Graduate School. The Thirty Third International Conference on Software Engineering and Knowledge Engineering (SEKE 2021), 2021-07-01 - 2021-07-10, Pittsburgh, USA (Online). doi: 10.18293/SEKE2021-162. ISBN 1-891706-52-7. ISSN 2325-9000.
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Kurzfassung
Software version control platforms, such as GitHub, host millions of open-source software projects. Due to their diversity, these projects are an appealing realm for discovering software trends. In our work, we seek to quantify synergy between software projects by connecting them via their similar as well as different software features. Our approach is based on the Literature-Based-Discovery (LBD), originally developed to uncover implicit knowledge in scientific literature databases by linking them through transitive connections. We tested our approach by conducting experiments on 13,264 GitHub (open-source) Python projects. Evaluation, based on human ratings of a subset of 90 project pairs, shows that our developed models are capable of identifying potential synergy between software projects by solely relying on their short descriptions (i.e. readme files).
| elib-URL des Eintrags: | https://elib.dlr.de/141909/ | ||||||||||||||||
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| Dokumentart: | Konferenzbeitrag (Anderer) | ||||||||||||||||
| Zusätzliche Informationen: | Will be published in July 1, 2021 | ||||||||||||||||
| Titel: | Quantifying Synergy between Software Projects using README Files Only | ||||||||||||||||
| Autoren: |
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| Datum: | Juli 2021 | ||||||||||||||||
| Erschienen in: | 33rd International Conference on Software Engineering and Knowledge Engineering, SEKE 2021 | ||||||||||||||||
| Referierte Publikation: | Ja | ||||||||||||||||
| Open Access: | Ja | ||||||||||||||||
| Gold Open Access: | Nein | ||||||||||||||||
| In SCOPUS: | Ja | ||||||||||||||||
| In ISI Web of Science: | Nein | ||||||||||||||||
| Band: | 33 | ||||||||||||||||
| DOI: | 10.18293/SEKE2021-162 | ||||||||||||||||
| Verlag: | KSI Research Inc. and Knowledge Systems Institute Graduate School | ||||||||||||||||
| Name der Reihe: | Proceedings of the 33rd International Conference on Software Engineering and Knowledge Engineering | ||||||||||||||||
| ISSN: | 2325-9000 | ||||||||||||||||
| ISBN: | 1-891706-52-7 | ||||||||||||||||
| Status: | akzeptierter Beitrag | ||||||||||||||||
| Stichwörter: | repository mining, natural language processing, recommendation system, readme cluster | ||||||||||||||||
| Veranstaltungstitel: | The Thirty Third International Conference on Software Engineering and Knowledge Engineering (SEKE 2021) | ||||||||||||||||
| Veranstaltungsort: | Pittsburgh, USA (Online) | ||||||||||||||||
| Veranstaltungsart: | internationale Konferenz | ||||||||||||||||
| Veranstaltungsbeginn: | 1 Juli 2021 | ||||||||||||||||
| Veranstaltungsende: | 10 Juli 2021 | ||||||||||||||||
| Veranstalter : | http://ksiresearchorg.ipage.com/seke/seke21.html | ||||||||||||||||
| HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||
| HGF - Programm: | Raumfahrt | ||||||||||||||||
| HGF - Programmthema: | Technik für Raumfahrtsysteme | ||||||||||||||||
| DLR - Schwerpunkt: | Raumfahrt | ||||||||||||||||
| DLR - Forschungsgebiet: | R SY - Technik für Raumfahrtsysteme | ||||||||||||||||
| DLR - Teilgebiet (Projekt, Vorhaben): | R - Aufgaben SISTEC, R - Analytik und Visualisierung großer Raumfahrt-Softwaresysteme | ||||||||||||||||
| Standort: | Köln-Porz , Oberpfaffenhofen | ||||||||||||||||
| Institute & Einrichtungen: | Institut für Softwaretechnologie Institut für Softwaretechnologie > Intelligente und verteilte Systeme | ||||||||||||||||
| Hinterlegt von: | El Baff, Roxanne | ||||||||||||||||
| Hinterlegt am: | 26 Mai 2021 12:05 | ||||||||||||||||
| Letzte Änderung: | 24 Apr 2024 20:42 |
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