1. Prerequisite:

• Install Docker

  • To know more about Docker - 12 mins video to understand Docker: YouTube Bilibili
  • If you have installation problems on Windows, please refer to windows-docker-problem-solutions

• And you can choose one IDE below

  • Install VSCode
    • For further using and learning VSCode - Learn to code with VSCode
  • Install PyCharm
    • For further using and learning Pycharm - Learn to code with Pycharm

• Download Docker image according to your environment

2. Run with VSCode

If you encounter some problem, please check this document Trouble-Shooting-for-IDE.

2.1 Working with VSCode in Docker containers

Install extensions in VSCode

*To install the extension, open the Extensions view (MAC: ⇧⌘X, Windows: Ctrl+Shift+X, Linux: Ctrl+Shift+X)

• Extension(1): Docker extension
  • Search for docker to filter results and select Docker extension authored by Microsoft.

• Extension(2): Remote Containers extension
  • Search for dev container to filter results and select extension authored by Microsoft.

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Load Docker container in VSCode

Right click the container item and select 'Attach Visual Studio Code'

If you can't see the working directory, please select file -> open (folder)... then enter the /home/SVF-tools/Software-Security-Analysis

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Install/Enable Python Debugger extension in container

*To install the extension, open the Extensions view (MAC: ⇧⌘X, Windows: Ctrl+Shift+X, Linux: Ctrl+Shift+X)

Search for Python Debugger and select Docker extension authored by Microsoft.

The labs use Jupyter Notebook, which displays code and output together. First, install the ipykernel package from pip, using your command line of choice (this is required for the VS Code Jupyter extension to work properly):

pip install ipykernel

Search for Jupyter and install the extension pack authored by Microsoft:

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2.2 Run and debug your program

• VSCode's built-in debugger helps your editing, compilation and debugging.

• Check that the Python interpreter should be /usr/bin/python3 or the virtual environment where you installed pysvf. Click Search - Show and Run Commands - Python: Select Interpreter, and choose a Python 3.8-3.12 interpreter.

• Software-Security-Analysis has prepared configurations in launch.json in .vscode folder to debug test.py in ${workspaceFolder}/Assignment-1/Python folder.

Switching programs

When working on different labs/assignments, change the "program" and "args" fields in launch.json

Lab/Assignment	"program"	"args"
Assignment-1	"${workspaceFolder}/Assignment-1/Python/test.py"	"-icfg", "Assignment-1/Tests/testcases/icfg/test1.ll" "-pta", "Assignment-1/Tests/testcases/pta/test1.ll" "-taint", "Assignment-1/Tests/testcases/taint/test1.ll"
Assignment-2	"${workspaceFolder}/Assignment-2/Python/test-sse.py"	"Assignment-2/Tests/testcases/sse/test1.ll"
Assignment-3	"${workspaceFolder}/Assignment-3/Python/test-ae.py"	"Assignment-3/Tests/stmt.ll" "Assignment-3/Tests/buf_overflow.ll" "Assignment-3/Tests/null_deref.ll"

3. Run with PyCharm

PyCharm is a powerful Python IDE. This section explains how to set up your project and work with pysvf using PyCharm on Linux/macOS and Windows (via Docker).

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3.1 Install PyCharm

• Download and install the Community or Professional edition from the official website:
  👉 https://www.jetbrains.com/pycharm/download

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3.2 Install Required Python Packages

If you're using Linux or macOS, you can install pysvf directly in PyCharm terminal:

python3 -m pip install pysvf

For Windows users, follow these steps to configure PyCharm with Docker:

1. Navigate to File > Settings > Project > Python Interpreter

2. Click Add Interpreter and select On Docker

3. Select Pull or use existing, enter svf-tools/software-security-analysis in the Image tag field, then click Next

4. If no errors appear in the output field, click Next

5. Click Create to finish the setup

6. Return to the Python Interpreter settings. If you see a remote Python interpreter from svf-tools/software-security-analysis, the configuration was successful