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online appendix for the submission
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.gitignore

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# General
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.DS_Store
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.AppleDouble
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.LSOverride
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# Icon must end with two \r
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Icon
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# Thumbnails
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._*
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# Files that might appear in the root of a volume
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.DocumentRevisions-V100
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.fseventsd
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.Spotlight-V100
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.TemporaryItems
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.Trashes
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.VolumeIcon.icns
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.com.apple.timemachine.donotpresent
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# Directories potentially created on remote AFP share
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.AppleDB
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.AppleDesktop
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Network Trash Folder
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Temporary Items
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.apdisk

README.md

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# Configuration Smells in Continuous Delivery Pipelines: A Linter and A Six-Month Study on GitLab (Replication Package)
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## DATASETS (datasets.zip)
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**Warning** Direct links to the opened issues are omitted according to the double-blind policy. Furthermore, we discourage people browsing issues on GitLab projects that might reveal the author identities.
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- `analyzedprojects.csv`: all starred Gitlab projects that are no forks.
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- `dataset.csv`: all projects (from previous set) that have a .gitlab.yml file.
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- `rq1-comment-sorting/`: this folder contains all the material related to the card sorting performed on the received comments. The found labels (`card-sorting-labels.csv`) and how the two coders agreed (`card-sorting-agreement.csv`). This folder also contains a summary of the reasons for rejection.
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- `rq1-cdsmells.csv`: info about the opened issues and the corresponding reactions/fixes.
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- `rq2-precision.csv`: the results of the manual inspection of issues to compute the precision.
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- `rq2-recall/`: this folder contains the selected sample of projects (`recall-sample.csv`) and the results of the recall analysis (`recall-results.csv`).
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- `rq3-analysis/`: it contains all the files to compute the RQ3 and a summary of RQ3 results.
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- `rq3-results.csv`: the list of all anti-patterns having "dataset.csv" projects as input.
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- `dataset_yml-update.csv`: "dataset.csv" projects with info about the .gitlab-ci.yml lenght and their (updated) existence on GitLab.
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- `tools-to-exclude-fuzzyversion.txt`: the list of the tools excluded from fuzzy-version detection.
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- `good_bad_cd-practices.csv`: all the good and bad practices that we collected from the Foundations part of Humble's book.
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## SCRIPTS (scripts.zip)
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Note: please install all the required dependencies.
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- `study-results.py`: this script analyzes and computes the results of the research questions.
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- `likert-scaled-reactions.R`: this script is used to compute Figure 4 (`reactions.csv` that is generated by "study-results.py" must be passed as input file).
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## CD-Linter Implementation (cd-linter-code.zip)
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It contains the source code of our linter (all packages have been anonymized).

cd-linter-code.zip

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datasets.zip

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scripts.zip

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