Docker-related Research Repository

This project was created to be a public repository to support Docker-related research and study. You are welcome to share other research with us. To add a new paper, you can simply add an issue or a pull request.

2022

• Fixing Dockerfile Smells: An Empirical Study.

  • Giovanni Rosa, Simone Scalabrino and Rocco Oliveto.
  • In ICSME. source

• Dockerlive: A live development environment for Dockerfiles.

  • D Reis, FF Correia.
  • In VL/HCC. source

• Understanding and Predicting Docker Build Duration: An Empirical Study of Containerized Workflow of OSS Projects.

  • Yiwen Wu, Yang Zhang, Kele Xu, Tao Wang, and Huaimin Wang.
  • In ASE. source

• An empirical study on self-admitted technical debt in Dockerfiles.

  • Azuma H, Matsumoto S, Kamei Y, et al.
  • In ESE. source

• Recommending Base Image for Docker Containers based on Deep Configuration Comprehension.

  • Zhang Y*, Zhang Y*, Mao X, et al.
  • In SANER. source

• A Preliminary Analysis of GPL-Related License Violations in Docker Images.

  • Higashi Y, Fukui K, Ohira M.
  • In SANER. source

2021

• Type-2 Code Clone Detection for Dockerfiles.

  • Tsuru T, Nakagawa T, Matsumoto S, Higo Y, Kusumoto S.
  • In IWSC. source

• Refactorings and Technical Debt in Docker Projects: An Empirical Study.

  • Ksontini E, Kessentini M, Ferreira T N, et al.
  • In ASE. source

• A study of how Docker Compose is used to compose multi-component systems.

  • Ibrahim M H, Sayagh M, Hassan A E.
  • In ESE. source

• Developing Docker and Docker-Compose Specifications: A Developers’ Survey.

  • Reis D, Piedade B, Correia F F, et al.
  • In IEEE Access. source

• DockerGen: A Knowledge Graph based Approach for Software Containerization.

  • Ye H, Zhou J, Chen W, et al.
  • In COMPSAC. source

• Revisiting Dockerfiles in Open Source Software Over Time.

  • Kalvin Eng, Abram Hindle.
  • In MSR. source

• A multi-dimensional analysis of technical lag in Debian-based Docker images.

  • Ahmed Zerouali, Tom Mens, Alexandre Decan, Jesus Gonzalez-Barahona, Gregorio Robles.
  • In EMSE. source

• Shipwright: A Human-in-the-Loop System for Dockerfile Repair.

  • Jordan Henkel, Denini Silva, Leopoldo Teixeira, Marcelo d’Amorim, Thomas Reps.
  • In ICSE. source

• Should you Upgrade Official Docker Hub Images in Production Environments?

  • Sara Gholami, Hamzeh Khazaei, Cor-Paul Bezemer.
  • In ICSE-NIER. source

2020

• Latest Image Recommendation Method for Automatic Base Image Update in Dockerfile.

  • Kitajima S, Sekiguchi A.
  • In ICSOC. source

• Using Configuration Semantic Features and Machine Learning Algorithms to Predict Build Result in Cloud-Based Container Environment.

  • Yiwen Wu*, Yang Zhang*, Junsheng Chang, Bo Ding, Tao Wang, Huaimin Wang.
  • In ICPADS. source

• Dockerfile Changes in Practice: A Large-Scale Empirical Study of 4,110 Projects on GitHub.

  • Yiwen Wu*, Yang Zhang*, Tao Wang, Huaimin Wang.
  • In APSEC. source

• A Large-scale Data Set and an Empirical Study of Docker Images Hosted on Docker Hub.

  • Lin, C.; Nadi, S.; and Khazaei, H.
  • In ICSME. source

• Too many images on DockerHub! How different are images for the same system?

  • M.H. Ibrahim, M. Sayagh, Hassan, A.E.
  • In ESE Journal. source

• Ten Simple Rules for Writing Dockerfiles for Reproducible Data Science.

  • Daniel Nüst, Vanessa Sochat, Ben Marwick, Stephen Eglen, Tim Head, Tony Hirst, Benjamin Evans.
  • In OSFPreprints. source

• Challenges in Docker Development: A Large-scale Study Using Stack Overflow.

  • Mubin Ul Haque, Leonardo Iwaya and Muhammad Ali Babar.
  • In ESEM conference. source

• A Dataset of Dockerfiles.

  • Jordan Henkel, Christian Bird, Shuvendu K. Lahiri, Thomas Reps.
  • In MSR conference. source

• An Empirical Study of Build Failures in the Docker Context.

  • Yiwen Wu*, Yang Zhang*, Tao Wang, Huaimin Wang.
  • In MSR conference. source

• Characterizing the Occurrence of Dockerfile Smells in Open-Source Software: An Empirical Study.

  • Yiwen Wu, Yang Zhang, Tao Wang, Huaimin Wang.
  • In IEEE Access Journal. source

• Exploring the Relationship between Dockerfile Quality and Project Charateristics.

  • Yiwen Wu.
  • In ICSE-SRC conference. source

• Learning from, Understanding, and Supporting DevOps Artifacts for Docker.

  • Jordan Henkel, Christian Bird, Shuvendu K. Lahiri, Thomas Reps.
  • In ICSE conference. source

2019

• Handling Duplicates in Dockerfiles Families: Learning from Experts.

  • Mohamed A. Oumaziz, Jean-Rémy Falleri, Xavier Blanc, Tegawendé F. Bissyandé, Jacques Klein.
  • In ICSME conference. source

• FastBuild: Accelerating Docker Image Building for Efficient Development and Deployment of Container.

  • Zhuo Huang, Song Wu, Song Jiang, and Hai Jin.
  • In MSST conference. source

• Wale: A solution to share libraries in Docker containers.

  • Fabio D’Urso, Corrado Santoro, Federico Fausto Santoro.
  • In FGCS Journal. source

• Large-Scale Analysis of the Docker Hub Dataset.

  • Nannan Zhao, Vasily Tarasov, Hadeel Albahar, Ali Anwar, Lukas Rupprecht, Dimitrios Skourtis, Amit S. Warke, Mohamed Mohamed, and Ali R. Butt.
  • In Cluster conference. source

• DOCKERFINDER: Multi-attribute search of Docker images.

  • Antonio Brogi, Davide Neri, and Jacopo Soldani.
  • In IC2E conference. source

• An Empirical Case Study on the Temporary File Smell in Dockerfiles.

  • Zhigang Lu, Jiwei Xu, Yuewen Wu, Zhigang Lu, Tao Wang, Tao Huang.
  • In IEEE Access Journal. source

• Dockerfile TF Smell Detection Based on Dynamic and Static Analysis Methods.

  • Jiwei Xu, Yuewen Wu, Zhigang Lu, Tao Wang.
  • In COMPSAC conference. source

• On The Relation Between Outdated Docker Containers, Severity Vulnerabilities and Bugs.

  • Zerouali A, Mens T, Robles G, Gonzalez-Barahona J.
  • In SANER conference. source

• SemiTagRec: A Semi-supervised Learning Based Tag Recommendation Approach for Docker Repositories.

  • Jiahong Zhou, Wei Chen, Guoquan Wu, Jun Wei.
  • In ICSR conference. source

2018

• Explaining Successful Docker Images Using Pattern Mining Analysis.

  • Riccardo Guidotti, Jacopo Soldani, Davide Neri, Antonio Brogi.
  • In STAF conference. source

• Helping Your Docker Images to Spread Based on Explainable Models.

  • Riccardo Guidotti, Jacopo Soldani, Davide Neri, Antonio Brogi, Dino Pedreschi.
  • In ECML PKDD conference. source

• STAR: A Specialized Tagging Approach for Docker Repositories.

  • Kang Yin, Wei Chen, Jiahong Zhou, Guoquan Wu, Jun Wei.
  • In APSEC conference. source

• Wale: A Dockerfile-Based Approach to Deduplicate Shared Libraries in Docker Containers.

  • Santoro, Corrado, Fabrizio Messina, Fabio D’Urso, and Federico Fausto Santoro.
  • In DASC/PiCom/DataCom/CyberSciTech conference. source

• One Size Does Not Fit All: An Empirical Study of Containerized Continuous Deployment Workflows.

  • Zhang, Y., Vasilescu, B., Wang, H. and Filkov, V.
  • In ESEC/FSE conference. source

• An Insight Into the Impact of Dockerfile Evolutionary Trajectories on Quality and Latency.

  • Zhang, Y., Yin, G., Wang, T., Yu, Y. and Wang, H.
  • In COMPSAC conference. source

• A clustering-based approach for mining dockerfile evolutionary trajectories.

  • Zhang, Y., Wang, H. and Filkov, V.
  • In SCIS Journal. source

• Structured Information on State and Evolution of Dockerfiles on GitHub.

  • Schermann, G., Zumberi, S. and Cito, J.
  • In MSR conference. source

• Mining container image repositories for software configuration and beyond.

  • Xu, T. and Marinov, D.
  • In ICSE-NIER conference. source

• RUDSEA: recommending updates of Dockerfiles via software environment analysis.

  • Hassan, F., Rodriguez, R. and Wang, X.
  • In ASE conference. source

• D-Tagger: A Tag Recommendation Approach for Docker Repositories.

  • Yin, K., Zhou, J., Chen, W., Wu, G., Zhu, J. and Wei, J.
  • In Internetware conference. source

2017

• An empirical analysis of the Docker container ecosystem on GitHub.
  • Cito, J., Schermann, G., Wittern, J.E., Leitner, P., Zumberi, S. and Gall, H.C.
  • In MSR conference. source