• analyzed_projects_all.csv contains in CSV format the list of all cloned projects at the time of this study.

  • repo_name is the repository name;
  • last_checkout is the hash of the last commit available at the time of the clone, and;
  • date is the date of the latest available commit.

• detailed-database is a folder containing the two complete datasets we defined.

  • overall.json contains all the instances of our dataset (1,930);
  • language-filtered.json contains 1,115 instances involving files in the following languages: C, Python, C++, JavaScript, Java, PHP, Ruby, and C#. Both these datasets are JSON arrays. Each element has the following structure:
    • id is a unique ID used during the construction phase, it is a univocal value for every entry;
    • repository is the repository name as hosted in GitHub (owner/project-name);
    • fix contains information about the fix, including:
      • commit: meta-data about the commit, including:
        • hash: commit hash;
        • message: commit message;
        • author: commit author;
        • url: GitHub API url with complete information about the commit;
      • files: an array of files modified in the fix commit; each element provides:
        • name: name of the modified file after the commit (this is not the complete path, just the file name);
        • old_path/new_path: path of the file before and after the commit;
        • lang: extension of the file (indicating the programming language);
        • lines_added/lines_deleted: lists of line numbers added/deleted;
        • change_type: type of change (one of the following: "MODIFY"/"ADD"/"RENAME"/"DELETE");
    • bugs contains the list of bug-inducing-commits for the fix; each element includes:
      • commit: meta-data about the commit, including:
        • hash: commit hash;
        • message: commit message;
        • author: commit author;
        • url: GitHub API url with complete information about the commit;
      • files: an array of files modified in the fix commit; each element provides:
        • name: name of the modified file after the commit (this is not the complete path, just the file name);
        • old_path/new_path: path of the file before and after the commit;
        • lang: extension of the file (indicating the programming language);
        • lines_added/lines_deleted: lists of line numbers added/deleted;
        • change_type: type of change (one of the following: "MODIFY"/"ADD"/"RENAME"/"DELETE");
    • issue_urls is a list of URLs of issues referenced in the fix commit;
    • earliest_issue_date is the date of the earliest issue referenced in the fix commit (YYYY-MM-DDTHH:MM:SS);
    • best_scenario_issue_date represents the date of an ideal issue reported for the bug; it is the date of the last bug inducing commit incremented by 60 seconds (YYYY-MM-DDTHH:MM:SS).

• json-input-raw is a folder containing four datasets used as input for our experimentations, derived from language-filtered.json.

  • bugfix_commits_all.json and bugfix_commits_issues_only.json contain 1,115 and 129 instances in JSON format, respectively.
  • bugfix_commits_all_java.json and bugfix_commits_issues_only_java.json contain 80 and 10 instances in JSON format, respectively.
    These datasets represent the input list of the selected fix commits and its relative list of bug-inducing commits, other than the following additional information used in our SZZ evaluation.
    • id is a unique ID used during the construction phase, it is a univocal value for every entry;
    • repo_name is the repository name as hosted in GitHub;
    • fix_commit_hash is the commit's hash of the selected fix;
    • bug_commit_hash is a list of bug-inducing commits;
    • earliest_issue_date is a string containing the timestamp of the earliest issue (YYYY-MM-DDTHH:MM:SS);
    • best_scenario_issue_date represents the date of an ideal issue reported for the bug; it is the date of the last bug inducing commit incremented by 60 seconds (YYYY-MM-DDTHH:MM:SS);
    • issue_urls s a list of URLs of issues referenced in the fix commit;
    • language is a list of the programming languages of the files impacted by fix commit.

• cloned is a placeholder folder where git repositories must be copied (or cloned) to replicate this work. See instruction below.

• json-output-raw is a folder with a list of JSON files that contain our pre-calculated results for each SZZ algorithm.

• scripts is a folder that contains all scripts created to post-processing or analyze our data.

• tools is a folder that contains a snapshot of developed codes. For new studies, please use the latest version of PySZZ.

• results is a folder that contains all calculated metrics, as Precision, Recall, F-measure, etc.

The following are the instructions needed to execute our suite of tools and generate our results. This example refers to the B-SSZ variant, but any other algorithm can be reproduced by changing the input arguments as detailed in the original guide. See tools/pyszz.zip for more instructions.

• Preparing input data. As the first step you need to clone the git repository of every project. You can rely on the following approach.

  • As an alternative, you can clone into cloned folder each repository and then checkout the list of commit's hashes contained in analyzed_projects_all.csv and analyzed_projects_issues_only.csv. This recreates the exact same conditions of our experiment.

• Running SZZ. PySZZ (see tools/pyszz.zip for a replication snapshot, and check the URL for the latest version) is a free open-source suite of tools used to implement in Python all SZZ major variants. You can run a specific variant by passing a pre-defined yml file or experiment custom inputs. E.g., conf/bszz.yml activates B-SZZ variant.

python3 main.py json-input-raw/bugfix_commits_all.json conf/bszz.yml cloned runs B-SZZ algorithm.

Where:

• json-input-raw/bugfix_commits_all.json is the input list of fixes;
• conf/bszz.yml is a pre-defined list of settings used to activate a specific variant (see tools/pyszz.zip for more details);
• cloned is the folder containing a list of pre-cloned repositories.

NOTE. SZZUnleashed and OpenSZZ are not part of PySZZ suite. We adapted the original implementations to our input formats.

• The SZZUnleashed implementation has been forked to handle our input formant and add parallel support SZZUnleashed-adapted (See tools/szz-unleashed.zip as a snapshot of our adapter)
• The OpenSZZ implementation has been forked to exclude the Jira filter OpenSZZ (See tools/open-szz.zip as a snapshot of our adapter) OpenSZZ needs a post-processing to adapt the generated results to our JSON format. See below OpenSZZ post processing script

Both snapshots tools/szz-unleashed.zip and tools/open-szz.zip contain the instructions to use our adapters.

json-output-raw contains a list of JSON file generated by each SZZ variant.

Specifically, bic_<algorithm-name>_bugfix_commits_all.json and bic_<algorithm-name>_bugfix_commits_issues_only.json refer to the output of <algorithm-name> SZZ variant. Instead, bic_<algorithm-name>_bugfix_commits_all-filter.json and bic_<algorithm-name>_bugfix_commits_issues_only-filter.json is the post filtered output when the filter on issue data is applied.

We use ruby postfilter.rb <json-output> <cloned> to post-process bic_<algorithm-name>_bugfix_commits_all.json and bic_<algorithm-name>_bugfix_commits_issues_only.json and generate bic_<algorithm-name>_bugfix_commits_all-filter.json and bic_<algorithm-name>_bugfix_commits_issues_only-filter.json, as a reduced list of datapoints filter by issue's date.

• postfilter.rb is out ruby script used to parse the output of any SZZ algorithm to filter out bic commits that do not respect the issue date condition.
• <json-output> is the input folder containing the list of JSON files produced by PySZZ;
• <cloned> is the path to the pre-cloned (or checked out) repositories.

overlap.py is a Python script with embedded input paths that can be used to calculate Recall, Precision, F-measure, and overlap. You may need to adapt base_path global variable to point to your result's directory. E.g., base_path = "json-output-raw/" analyzes the study's results.

This tool produces:

• <dataset>-recall-precision.csv lists Precision, Recall, F-measure, total number of correct instances (our oracle), and total number of identified instances;

• <dataset>-overlap_vi_vj.csv lists the overlap, the total number of BIC uniquely identified, the total number of correctly identified, and the union of all BIC correctly identified by all models;

• <dataset>-overlap_vi_but_others.csv is a CSV version of the heatmap for the overlap comparison.

• <dataset>-not-identified.csv summarizes the not found BICs;

• <dataset>-heatmap.pdf as reported in the manuscript.

• wrong is a subfolder with a list of CSV files containing the wrongly identified BIC with a link to GitHub FIX commit.

OpenSZZ produces three files for each analyzed instance. E.g., AIFDR_inasafe_BugFixingCommit.csv, AIFDR_inasafe_BugInducingCommits.csv, and AIFDR_inasafe.txt.

To transform all these CSV files in a single JSON file compatible to overlap.py we create a small script openszz_file_refactoring.py.

python3 openszz_file_refactoring.py <oracle> <openszz-issue> <bic_open_bugfix_commits_issues_only.json>

Where:

• <oracle> is the list of fixes. E.g., json-input-raw/bugfix_commits_all.json;
• <openszz-issue> is the folder path where openSZZ produces its results;
• <bic_open_bugfix_commits_issues_only.json> is the destination file output where to store in JSON format openSZZ bug-inducing commits;