arcsysu/YatCC
May 2025 – Apr 2026
2 Months active
Languages Used
C++PythonShellCMake
Technical Skills
AI IntegrationBuild System ConfigurationC++ DevelopmentCMakeContainerizationLLVM IR Analysis
Zhou7D663
PROFILE
Zhou7d663
Worked on the arcsysu/YatCC repository to deliver two core features over a two-month period, focusing on AI-driven compiler optimization and enhanced testing workflows. Developed an AI-enabled LLVM optimization pipeline by integrating Python and C++ using pybind11, allowing dynamic sequencing of LLVM passes guided by large language model analysis. Updated build artifacts and CMake configurations to support these new capabilities. Additionally, implemented a DIY testing workflow that enables per-test-case compilation and scoring without caching, introducing new CLI options for greater test isolation and configurability. Leveraged skills in C++, Python, CMake, and containerization to improve both optimization and testing processes.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
2,038
Activity Months2
Your Network
11 peopleShared Repositories
11
Work History
April 2026
1 Commits • 1 Features
Apr 1, 2026April 2026 — arcsysu/YatCC: Implemented the DIY Testing Workflow for Task3, enabling compile and score of individual test cases without caching and adding new CLI options to control caching behavior and scoring for DIY test cases. This results in faster, more reliable local testing and supports rapid experimentation for Task3.
1 Commits • 1 Features
Apr 1, 2026April 2026 — arcsysu/YatCC: Implemented the DIY Testing Workflow for Task3, enabling compile and score of individual test cases without caching and adding new CLI options to control caching behavior and scoring for DIY test cases. This results in faster, more reliable local testing and supports rapid experimentation for Task3.
April 2026
May 2025
1 Commits • 1 Features
May 1, 2025May 2025 monthly summary for arcsysu/YatCC focusing on AI-driven LLVM optimization passes. Key feature delivered: AI-driven LLVM optimization passes integrated with Python-C++ bindings using pybind11, enabling AI-assisted dynamic sequencing of LLVM passes guided by LLM analysis. Major bugs fixed: none reported this month. Overall impact: established a scalable, AI-enabled optimization pipeline within YatCC, updated build artifacts to support the new passes, and laid the groundwork for Task 4 with AI-driven optimizations. Technologies/skills demonstrated: Python-C++ interoperability via pybind11, cross-language integration, AI-assisted compiler workflows, LLVM pass sequencing, and build-system updates.
May 2025
1 Commits • 1 Features
May 1, 2025May 2025 monthly summary for arcsysu/YatCC focusing on AI-driven LLVM optimization passes. Key feature delivered: AI-driven LLVM optimization passes integrated with Python-C++ bindings using pybind11, enabling AI-assisted dynamic sequencing of LLVM passes guided by LLM analysis. Major bugs fixed: none reported this month. Overall impact: established a scalable, AI-enabled optimization pipeline within YatCC, updated build artifacts to support the new passes, and laid the groundwork for Task 4 with AI-driven optimizations. Technologies/skills demonstrated: Python-C++ interoperability via pybind11, cross-language integration, AI-assisted compiler workflows, LLVM pass sequencing, and build-system updates.
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance70.0%
AI Usage50.0%
Skills & Technologies
Programming Languages
C++CMakePythonShell
Technical Skills
AI IntegrationBuild System ConfigurationC++ DevelopmentCMakeCMake build systemContainerizationLLVM IR AnalysisLLVM Pass DevelopmentPybind11Python DevelopmentPython scriptingtesting
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