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Quantifying Synergy between Software Projects using README Files Only

El Baff, Roxanne and Santhanam, Sivasurya and Hecking, Tobias (2021) Quantifying Synergy between Software Projects using README Files Only. In: Proceedings of the 33rd International Conference on Software Engineering and Knowledge Engineering, 33. KSI Research Inc. and Knowledge Systems Institute Graduate School. The Thirty Third International Conference on Software Engineering and Knowledge Engineering (SEKE 2021), 1-10 July, Pittsburgh, USA (Online). doi: 10.18293/SEKE2021-162.

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Abstract

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).

Item URL in elib:https://elib.dlr.de/141909/
Document Type:Conference or Workshop Item (Other)
Additional Information:Will be published in July 1, 2021
Title:Quantifying Synergy between Software Projects using README Files Only
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
El Baff, RoxanneGerman Aerospace Center (DLR)https://orcid.org/0000-0001-6661-8661
Santhanam, SivasuryaGerman Aerospace Center (DLR)UNSPECIFIED
Hecking, TobiasGerman Aerospace Center (DLR)UNSPECIFIED
Date:July 2021
Journal or Publication Title:Proceedings of the 33rd International Conference on Software Engineering and Knowledge Engineering
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Volume:33
DOI :10.18293/SEKE2021-162
Publisher:KSI Research Inc. and Knowledge Systems Institute Graduate School
Series Name:Proceedings of the 33rd International Conference on Software Engineering and Knowledge Engineering
Status:Accepted
Keywords:repository mining, natural language processing, recommendation system, readme cluster
Event Title:The Thirty Third International Conference on Software Engineering and Knowledge Engineering (SEKE 2021)
Event Location:Pittsburgh, USA (Online)
Event Type:international Conference
Event Dates:1-10 July
Organizer:http://ksiresearchorg.ipage.com/seke/seke21.html
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space System Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Space System Technology
DLR - Research theme (Project):R - Tasks SISTEC, R - Analytics and visualization of large space software systems
Location: Köln-Porz , Oberpfaffenhofen
Institutes and Institutions:Institute for Software Technology
Institute for Software Technology > Intelligent and Distributed Systems
Deposited By: El Baff, Roxanne
Deposited On:26 May 2021 12:05
Last Modified:26 May 2021 12:05

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