Samenvatting
Context: While industrial use of UML was studied intensely, little is known about UML use in Free/Open Source Software (FOSS) projects. Goal: We aim at systematically mining GitHub projects to answer the question when models, if used, are created and updated throughout the whole project's life-span. Method: We present a semi-automated approach to collect UML stored in images, .xmi, and .uml files and scanned ten percent of all GitHub projects (1.24 million). Our focus was on number and role of contributors that created/updated models and the time span during which this happened. Results: We identified and studied 21 316 UML diagrams within 3 295 projects. Conclusion: Creating/updating of UML happens most often during a very short phase at the project start. For 12% of the models duplicates were found, which are in average spread across 1.88 projects. Finally, we contribute a list of GitHub projects that include UML files.
Originele taal-2 | Engels |
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Titel | Proceedings - 19th ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS 2016 |
Uitgeverij | Association for Computing Machinery, Inc |
Pagina's | 173-183 |
Aantal pagina's | 11 |
ISBN van elektronische versie | 9781450343213 |
DOI's | |
Status | Gepubliceerd - 2 okt. 2016 |
Extern gepubliceerd | Ja |
Evenement | 19th ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS 2016 - Saint-Malo, Frankrijk Duur: 2 okt. 2016 → 7 okt. 2016 |
Congres
Congres | 19th ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS 2016 |
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Land/Regio | Frankrijk |
Stad | Saint-Malo |
Periode | 2/10/16 → 7/10/16 |
Bibliografische nota
Publisher Copyright:© 2016 ACM.
Vingerafdruk
Duik in de onderzoeksthema's van 'The quest for open source projects that use UML: Mining GitHub'. Samen vormen ze een unieke vingerafdruk.Datasets
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Lindholmen Dataset of UML Models
Chaudron, M. R. V. (Ontwerper), Hebig, R. (Ontwerper), Robles, G. (Ontwerper) & Ho-Quang, T. (Ontwerper), Personal, 2017
Dataset