BugsInPy++ improves the scalability, reproducibility, and usability of the BugsInPy dataset. It is based on the modified BugsInPy by F. Aguilar, S. Grayson and D. Marinov. Below is the citation for the modified BugsInPy:

F. Aguilar, S. Grayson and D. Marinov, "Reproducing and Improving the BugsInPy Dataset," 2023 IEEE 23rd International Working Conference on Source Code Analysis and Manipulation (SCAM), Bogotá, Colombia, 2023, pp. 260-264, doi: 10.1109/SCAM59687.2023.00036.

Here is the repository of the modified BugsInPy by them:

https://github.com/reproducing-research-projects/BugsInPy

They did fantastic work on the BugsInPy dataset, but it has some limitations:

• It's scripts assume that the user uses their own Dockerfile. Thus, some file paths are hardcoded.
• Their conda environments use hash as a name, which is not very user friendly.
• Outputs of the tests are user friendly, but not machine friendly.
• Log messages are not enough to understand what is going on.
• If the conda environment is not existing, the script will fail.

Therefore, we fixed and improved these issues:

• The scripts can accept some environment variables to make it more flexible. See Environment Variables section.
• Now the conda environments are named with the project name and the bug id (e.g. youtube-dl_1). This makes it easier to understand which environment is used for which project and bug.
• The outputs of the tests are now more machine friendly. See Test results section.
• The log messages are optimized.
• bugsinpy-compile will create the conda environment if it does not exist. The other scripts for the testing will still fail to force the user to run bugsinpy-compile first.

• Python 3.8+
• Anaconda or Miniconda

BugsInPy++ is tested on Ubuntu 22.04 with Python 3.10 and Anaconda 2024.10.

Additionally, run following commands to install the required packages:

apt-get update
apt-get install -y git nano dos2unix build-essential

First, clone our BugsInPy repository:

git clone https://github.com/UNIST-LOFT/BugsInPyPP.git

Then, add the BugsInPy executables path to your PATH environment variable:

export PATH=$PATH:<bugsinpy_path>/framework/bin

In most cases, you can add this line to your ~/.bashrc, ~/.bash_aliases or ~/.bash_profile file to make it permanent.

That's it! Now you can use the BugsInPy commands from anywhere in your terminal.

bugsinpy-<command> --help

For example, run

bugsinpy-info --help

to print the help usage of bugsinpy-info command.

bugsinpy-checkout -p <project_name> -b <bug_id> -v <0/1> -w <workspace>

• -p <project_name>: Name of the project (e.g. youtube-dl).
• -b <bug_id>: Bug ID (e.g. 1).
• -v <0/1>: Buggy (0) or fixed (1) version.
• -w <workspace>: Workspace name in absolute path (e.g. $PWD/youtube-dl_1).

For example, to checkout the buggy version of bug 1 from the youtube-dl project, run:

bugsinpy-checkout -p youtube-dl -b 1 -v 0 -w $PWD/youtube-dl_1

bugsinpy-compile [-w <workspace>]

• -w <workspace>: Optional workspace name (e.g. youtube-dl_1). Default is current directory.

⚠️ Running bugsinpy-compile in parallel may cause issue related to urllib3 package.

For example to compile the project we checked out in the previous step, run:

bugsinpy-compile -w youtube-dl_1

or

cd youtube-dl_1
bugsinpy-compile

bugsinpy-test [-w <workspace>] [-t <test_case>] [-a]

• -w <workspace>: Optional workspace name (e.g. youtube-dl_1). Default is current directory.
• -t <test_case>: Run single test instead of all relevant tests. Format of the test case is dependent on the testing framework used in the project. To check the format, run bugsinpy-test --help.
• -a: Run all test cases instead of the relevant tests.

For example, to run relevant tests for the project we compiled in the previous step, run:

bugsinpy-test -w youtube-dl_1

or

cd youtube-dl_1
bugsinpy-test

To run a test whose ID is test.test_utils.TestUtil.test_match_str, run:

bugsinpy-test -w youtube-dl_1 -t test.test_utils.TestUtil.test_match_str

To run all tests, run:

bugsinpy-test -w youtube-dl_1 -a

After running relevant tests (i.e. default mode), the test results will be stored in the <workspace>/bugsinpy_test.txt file. In the file, it stores the results of the each test in the following format:

BugsInPy test: <test_command>: <return_code>

Where <test_command> is the command used to run the test and <return_code> is the return code of the command.

In addition, the stdout and stderr of the command will be stored.

Also, it prints the results to the console in the same format, but without the stdout and stderr from the command.

After running a single test, the test results will be stored in the <workspace>/bugsinpy_singletest.txt file with the same format as above.

After running all tests, the test results will be stored in the <workspace>/bugsinpy_alltest.txt file. However, the format is different from the relevant tests and single test. It is dependent on the testing framework used in the project.

• CONDA_PATH: Root path of conda installation. Default is $HOME/anaconda3.

The bugsinpy-testall script automates the execution of the BugsInPy dataset, which contains bugs in various Python projects. The script reproduces the bugs, executes tests, and records the results. It enhances the reproducibility of Python projects by providing a standardized process for reproducing and testing bugs in different projects.

Here's a summary of how the script works:

1. The script takes command-line arguments to control its behavior. It provides options to display help, perform cleanup, and specify projects or ranges of bugs to reproduce and test.

2. It creates a temp/projects directory to store the output and logs.

3. The script iterates over the specified projects or all projects in the BugsInPy/projects directory.

4. For each project, it determines the range of bugs to reproduce and test.

5. It executes the tests for each bug by performing the following steps: a. Checks if the bug has already been tested and skips it if so. b. Sets up the environment for testing the buggy (0) version:

   • Uses bugsinpy-checkout to checkout the buggy version.
   • Activates the proper Python environment using Miniconda (specified in the bugsinpy_bug.info file).
   • Compiles the project (if required) and runs the tests using bugsinpy-test.
   • Check if the buggy version fails as expected for the test specific to the bug and save the output in the BugsInPy/projects/<repo>/bugs/<bugid>/bug_buggy.txt.
   • Updates the BugsInPy/projects/bugsinpy-index.csv with the results <repo>,<bugid>,buggy,fail c. The it proceeds to test the fixed (1) version:
   • Uses bugsinpy-checkout to checkout the fixed version.
   • Compiles the project (if required) and runs the tests.
   • Activates the proper Python environment using Miniconda (specified in the bugsinpy_bug.info file).
   • Compiles the project (if required) and runs the tests using bugsinpy-test.
   • Check if the fixed version pass as expected for the test specific to the bug and save the output in the BugsInPy/projects/<repo>/bugs/<bugid>/bug_fixed.txt.
   • Updates the BugsInPy/projects/bugsinpy-index.csv with the results <repo>,<bugid>,fixed,pass

6. The script deactivates the Conda environment and repeats the process for the next bug in the project.

The bugsinpy-testall script improves reproducibility by providing a standardized and automated approach to reproduce and test bugs in Python projects. It ensures that bugs are tested consistently across different projects, enabling easier verification of bug fixes and facilitating the replication of test results. By logging the output and test results, it helps track the status of bug reproduction and provides a central record for analysis and further investigation.