madeline-underwood/arm-learning-paths
Oct 2025 – Oct 2025
1 Month active
Languages Used
CMakefileMarkdown
Technical Skills
Arm StreamlineEmbedded SystemsLinux Kernel DevelopmentPerformance AnalysisProfiling
Yahya Abouelseoud
PROFILE
Yahya Abouelseoud
Yahya Abouelseoud developed a comprehensive Linux kernel profiling learning path for the madeline-underwood/arm-learning-paths repository, focusing on performance analysis and optimization. He guided developers through building and profiling both out-of-tree and in-tree kernel modules using Arm Streamline, with detailed documentation of workflows and advanced techniques. By incorporating the Statistical Profiling Extension (SPE), Yahya enabled deeper analysis of performance bottlenecks, supporting more effective performance engineering. His work, implemented in C and Makefile with supporting Markdown documentation, addressed onboarding challenges and provided a structured approach for developers to enhance kernel performance, reflecting a strong depth of technical understanding and practical application.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
633
Activity Months1
Your Network
568 people
Work History
October 2025
1 Commits • 1 Features
Oct 1, 2025Month: 2025-10 — Delivered a comprehensive Linux kernel profiling learning path using Arm Streamline, enabling developers to identify performance bottlenecks in both out-of-tree and in-tree kernel modules, and to leverage the Statistical Profiling Extension (SPE) for deeper analysis. This accelerates performance optimization, improves onboarding, and supports our platform's performance engineering goals.
1 Commits • 1 Features
Oct 1, 2025Month: 2025-10 — Delivered a comprehensive Linux kernel profiling learning path using Arm Streamline, enabling developers to identify performance bottlenecks in both out-of-tree and in-tree kernel modules, and to leverage the Statistical Profiling Extension (SPE) for deeper analysis. This accelerates performance optimization, improves onboarding, and supports our platform's performance engineering goals.
October 2025
Activity
Loading activity data...
Quality Metrics
Correctness100.0%
Maintainability100.0%
Architecture100.0%
Performance100.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
CMakefileMarkdown
Technical Skills
Arm StreamlineEmbedded SystemsLinux Kernel DevelopmentPerformance AnalysisProfiling
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline