Skip to content

Latest commit

 

History

History
54 lines (35 loc) · 1.63 KB

README.md

File metadata and controls

54 lines (35 loc) · 1.63 KB
Raw

SWARM-CG: Swiss Army Knife of Call Graph Micro-Benchmark

SWARM-CG (Swiss Army Knife of Call Graph Micro-Benchmark) aims to standardize the evaluation of call graph analysis tools by providing a rich set of call graph benchmarks. This repository contains code samples and associated ground truth across multiple languages, facilitating cross-language performance comparisons and discussions.

Features

  • Multi-language support: Benchmarks in various programming languages.
  • Ground truth annotations: Accurate call-graph information for each sample.
  • Tool evaluation: Framework for assessing static analysis tools.
  • Community-driven: Contributions from static analysis enthusiasts and experts.

Languages Supported

Our repository includes benchmarks for the following languages:

  • Java
  • Python
  • JavaScript

More languages will be added soon.

🐳 Running with Docker

1️⃣ Clone the repo

git clone https://github.com/ashwinprasadme/SWARM-CG/

2️⃣ Build Docker image

docker build -t swarmcg .

3️⃣ Run SWARM-CG

🕒 Takes about 30mins on first run to build Docker containers.

📂 Results will be generated in the results folder within the root directory of the repository. Each results folder will have a timestamp, allowing you to easily track and compare different runs.

🔧 run analysis on specific tools:

docker run \
      -v /var/run/docker.sock:/var/run/docker.sock \
      -v ./results:/app/results \
      -v ./src:/app/src \
      swarmcg --language python --benchmark_name pycg --tool llms

🛠️ Available options: pycg, ollama, llms