Explaining successful docker images using pattern mining analysis

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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.

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APA

Guidotti, R., Soldani, J., Neri, D., & Brogi, A. (2018). Explaining successful docker images using pattern mining analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11176 LNCS, pp. 98–113). Springer Verlag. https://doi.org/10.1007/978-3-030-04771-9_9

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