The dataset of our FSE2015 submission, which can be used to study the influence of CI adoption in GitHub.
##Data description The data is presented in CSV format and can be directly imported in R.
all_projects.csv: The summary of all the raw projects.
n_pr: Total number of pull requests;n_ci_after: Number of pull requests received after CI adoption;n_ci_after_tested: Number of pull requests tested by CI;
team_productivity.csv: The data of productivity study in project level.
ci_age_month: the relative time of CI adoption in months, ranging from −12 to +12;proj_age: Project age in month at that time;n_pr_open: Number of pull requests received during that month;n_pr_core: Number of pull requests submitted by core developers;n_pr_merged: Number of pull requests have been merged into the master branch;n_pr_unmerged: Number of pull requests have been rejected;n_core_merged: Number of pull requests, which are submitted by core developers, have been merged into the master branch;n_core_unmerged: Number of pull requests, which are submitted by core developers, have been rejected;team_size: Number of developers on the project’s core team at that time;test_files & test_loc: Number of test files and the number of source lines of code in test files;src_files & src_loc: Number of source files and the number of source lines of code in source files;n_star: Number of stars received by the project’s main repository at that time;n_fork: Number of project forks at that time;
project_quality.csv: The data of quality study.
n_issues: Number of issues received during that month;n_tag_issues: Number of issues tagged by developers;n_bug_issues: Number of bug related issues;n_core_issues: Number of issue submitted by core developers;n_core_bugs: Number of bug related issues submitted by core developers;
We will publish our programs later, which can be used to analyse our dataset.