rose-docker-build

What This Skill Does

The rose-docker-build skill provides an automated, containerized approach to compiling the complex ROSE source-to-source compiler framework. Because ROSE relies on specific legacy versions of the GCC toolchain (specifically 7-10), attempting to build it on modern host operating systems often results in compilation errors. This skill abstracts the complexity of Dockerfile configuration and container lifecycle management, allowing developers to build, test, and develop with ROSE in a stable, version-locked environment.

Installation

To integrate this skill into your OpenClaw environment, execute the following command in your terminal: clawhub install openclaw/skills/skills/chunhualiao/rose-docker-build-skill Ensure you have Docker Desktop or the Docker Engine installed and running on your host machine prior to installation, as this skill performs direct operations against the Docker daemon.

Use Cases

• Cross-Platform Compilation: Building the ROSE compiler on systems running Ubuntu 22.04 or later, which lack the required GCC versions.
• CI/CD Pipeline Setup: Creating reproducible build environments for ROSE research projects to ensure consistent output across different machines.
• Development Environment Isolation: Avoiding 'dependency hell' on your host system by keeping build-time dependencies, such as Boost and specific autotools versions, contained within the container image.
• Modernizing Build Workflows: Transitioning from legacy Autotools-based builds to modern CMake build systems while maintaining compatibility with the core compiler framework.

Example Prompts

1. "OpenClaw, please set up a new ROSE development environment using the Autotools configuration in a container."
2. "I need to rebuild ROSE using CMake. Can you execute the build process with the standard Release configuration?"
3. "The ROSE compilation failed on my system. Can you use the rose-docker-build skill to isolate the build and identify if it is a dependency issue?"

Tips & Limitations

• Resource Allocation: ROSE builds are notoriously memory-intensive. When using the CMake workflow, always ensure your Docker container is allocated at least 8GB of RAM; use -j4 flags to limit parallel threads if you experience OOM (Out of Memory) kills.
• Host Volume Mapping: The skill uses volume mapping to keep your source code on the host machine. Ensure you have write permissions to your local project directory.
• Build Speed: The initial build is time-consuming as it compiles the large ROSE codebase. Use incremental builds and maintain your container state to significantly reduce subsequent build times.
• CMake vs Autotools: While CMake is recommended for modern IDE integration, the Autotools workflow remains the most stable path for deep ROSE framework development.