Dataset for Characterizing the Occurrence of Dockerfile Smells in Open-Source Software

Dataset for Characterizing the Occurrence of Dockerfile Smells in Open-Source Software

Citation Author(s):
Yiwen
Wu
Yang
Zhang
Tao
Wang
Huaimin
Wang
Submitted by:
Yang Zhang
Last updated:
Sat, 11/16/2019 - 11:43
DOI:
10.21227/r9v8-4f07
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Abstract: 

Dockerfile plays an important role in the Docker-based containerization process, but many Dockerfile codes are infected with smells in practice. This dataset contains a collection of 6,334 projects to help developers gain some insights into the occurrence of Dockerfile smells. Those projects belong to 10 popular programming languages, i.e., Shell, Makefile, Ruby, PHP, Python, Java, HTML, CSS, JavaScript, and Go. 

Instructions: 

This dataset contains 6,334 projects, including their metadata (i.e., names, owner type, creation times, programming languages, number of stars, and number of contributors), and details of Dockerfile smells (i.e., number of instructions, number of overall smells, number of DL-smells, and number of SC-smells). 

Specifically, the metrics in the CSV dataset are:

  • project: the project name;

  • p_language: project’s programming language;

  • p_contributors_team: number of project contributors (submitted at least one commit);

  • p_created_at: project's creation date;

  • p_owner_type: type of the project owner, i.e., “Organization” or “User”;

  • p_stars: number of project stars;

  • p_github_age: number of days that have passed since a project has been hosted on GitHub until April 2018; 

  • d_instructions: number of instructions in a Dockerfile; 

  • d_smells: the volume number of all smells in a Dockerfile;

  • d_smells_dl: the volume number of DL-smells in a Dockerfile;

  • d_smells_sc: the volume number of SC-smells in a Dockerfile. 

Dataset Files

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[1] Yiwen Wu, Yang Zhang, Tao Wang, Huaimin Wang, "Dataset for Characterizing the Occurrence of Dockerfile Smells in Open-Source Software", IEEE Dataport, 2019. [Online]. Available: http://dx.doi.org/10.21227/r9v8-4f07. Accessed: Feb. 27, 2020.
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doi = {10.21227/r9v8-4f07},
url = {http://dx.doi.org/10.21227/r9v8-4f07},
author = {Yiwen Wu; Yang Zhang; Tao Wang; Huaimin Wang },
publisher = {IEEE Dataport},
title = {Dataset for Characterizing the Occurrence of Dockerfile Smells in Open-Source Software},
year = {2019} }
TY - DATA
T1 - Dataset for Characterizing the Occurrence of Dockerfile Smells in Open-Source Software
AU - Yiwen Wu; Yang Zhang; Tao Wang; Huaimin Wang
PY - 2019
PB - IEEE Dataport
UR - 10.21227/r9v8-4f07
ER -
Yiwen Wu, Yang Zhang, Tao Wang, Huaimin Wang. (2019). Dataset for Characterizing the Occurrence of Dockerfile Smells in Open-Source Software. IEEE Dataport. http://dx.doi.org/10.21227/r9v8-4f07
Yiwen Wu, Yang Zhang, Tao Wang, Huaimin Wang, 2019. Dataset for Characterizing the Occurrence of Dockerfile Smells in Open-Source Software. Available at: http://dx.doi.org/10.21227/r9v8-4f07.
Yiwen Wu, Yang Zhang, Tao Wang, Huaimin Wang. (2019). "Dataset for Characterizing the Occurrence of Dockerfile Smells in Open-Source Software." Web.
1. Yiwen Wu, Yang Zhang, Tao Wang, Huaimin Wang. Dataset for Characterizing the Occurrence of Dockerfile Smells in Open-Source Software [Internet]. IEEE Dataport; 2019. Available from : http://dx.doi.org/10.21227/r9v8-4f07
Yiwen Wu, Yang Zhang, Tao Wang, Huaimin Wang. "Dataset for Characterizing the Occurrence of Dockerfile Smells in Open-Source Software." doi: 10.21227/r9v8-4f07