deepflowio/deepflow
Nov 2025 – Nov 2025
1 Month active
Languages Used
CC++Rust
Technical Skills
C programmingC++ programmingLinux kernel developmentLuaMemory ManagementRust
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PROFILE
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Francis Liang developed advanced Lua profiling capabilities for the deepflowio/deepflow repository, focusing on performance, observability, and maintainability across architectures. He engineered an AArch64-optimized Lua profiler with enhanced stack unwinding and eBPF integration, supporting both LuaJIT and multiple Lua versions to broaden profiling coverage. His work included implementing a PID-based Lua probe detachment mechanism and refactoring the Rust crate to clarify Lua offsets handling, consolidating unsafe calls for safer, more maintainable code. Using C, Rust, and eBPF, Francis delivered features that enable safer live-profiling in production environments and simplify future maintenance, demonstrating depth in systems programming and performance profiling.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
4Total
Bugs
0
Commits
4
Features
3
Lines of code
3,590
Activity Months1
Your Network
69 peopleSame Organization
@mail.utoronto.ca46
Work History
November 2025
4 Commits • 3 Features
Nov 1, 2025Month: 2025-11. Delivered a set of Lua profiling capabilities across architectures with a focus on performance, observability, and maintainability. Key work includes AArch64-optimized Lua profiler with enhanced stack unwinding and eBPF integration, Lua detach capability with PID-based management, and a refactor of Lua offsets handling in Rust for clarity. These efforts broaden profiling coverage (LuaJIT and multiple Lua versions), enable safer live-profiling in production, and simplify future maintenance.
4 Commits • 3 Features
Nov 1, 2025Month: 2025-11. Delivered a set of Lua profiling capabilities across architectures with a focus on performance, observability, and maintainability. Key work includes AArch64-optimized Lua profiler with enhanced stack unwinding and eBPF integration, Lua detach capability with PID-based management, and a refactor of Lua offsets handling in Rust for clarity. These efforts broaden profiling coverage (LuaJIT and multiple Lua versions), enable safer live-profiling in production, and simplify future maintenance.
November 2025
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage30.0%
Skills & Technologies
Programming Languages
CC++Rust
Technical Skills
C programmingC++ programmingLinux kernel developmentLuaMemory ManagementRustRust developmentSystems ProgrammingeBPFperformance profilingsystem programming
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