Docker is on the rise in today's enterprise IT. It permits shipping applications inside portable containers, which run from so-called Docker images. Docker images are distributed in public registries, which also monitor their popularity. The popularity of an image directly impacts on its usage, and hence on the potential revenues of its developers. In this paper, we present a frequent pattern mining-based approach for understanding how to improve an image to increase its popularity. The results in this work can provide valuable insights to Docker image providers, helping them to design more competitive software products.

Explaining successful docker images using pattern mining analysis

Guidotti R;
2018

Abstract

Docker is on the rise in today's enterprise IT. It permits shipping applications inside portable containers, which run from so-called Docker images. Docker images are distributed in public registries, which also monitor their popularity. The popularity of an image directly impacts on its usage, and hence on the potential revenues of its developers. In this paper, we present a frequent pattern mining-based approach for understanding how to improve an image to increase its popularity. The results in this work can provide valuable insights to Docker image providers, helping them to design more competitive software products.
2018
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Inglese
STAF 2018
98
113
https://link.springer.com/chapter/10.1007/978-3-030-04771-9_9
Sì, ma tipo non specificato
25/06/2018
Toulouse
Docker Images
Pattern Mining Analysis
Explanation
4
open
Guidotti, R; Soldani, J; Neri, D; Brogi, A
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
   SoBigData Research Infrastructure
   SoBigData
   H2020
   654024
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/358452
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