awslabs/s2n-bignum
Jun 2025 – Jun 2025
1 Month active
Languages Used
ML
Technical Skills
ARM ArchitectureCo-simulationCompiler DesignCompiler DevelopmentFormal VerificationReverse Engineering
amanda-zx
PROFILE
Amanda-zx
Amanda expanded ARM model coverage in the awslabs/s2n-bignum repository by implementing support for the REV instruction across 32-bit and 64-bit registers, as well as adding LDURB, STURB, LDUR, and STUR load/store instructions with full decoding logic. She integrated these features using ML and applied skills in ARM architecture, compiler development, and co-simulation. Her work included developing co-simulation tests to validate instruction behavior, which improved emulator fidelity and reduced edge-case risk in cryptographic workloads. The depth of her contributions strengthened instruction-set completeness and enhanced the reliability of the project’s formal verification and reverse engineering workflows.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
51
Activity Months1
Your Network
1392 people
Work History
June 2025
2 Commits • 2 Features
Jun 1, 2025June 2025: Expanded the ARM model coverage in awslabs/s2n-bignum with two key feature-focused deliveries. Implemented REV instruction support for both 32-bit and 64-bit registers, and added LDURB, STURB, LDUR, and STUR (64-bit and 32-bit) with decoding logic and co-simulation tests. These changes increase instruction-set completeness, improve emulator fidelity, and reduce edge-case risk in cryptographic workloads. The work demonstrates strong ARM decoding, instruction modeling, test automation, and collaboration across the project.
2 Commits • 2 Features
Jun 1, 2025June 2025: Expanded the ARM model coverage in awslabs/s2n-bignum with two key feature-focused deliveries. Implemented REV instruction support for both 32-bit and 64-bit registers, and added LDURB, STURB, LDUR, and STUR (64-bit and 32-bit) with decoding logic and co-simulation tests. These changes increase instruction-set completeness, improve emulator fidelity, and reduce edge-case risk in cryptographic workloads. The work demonstrates strong ARM decoding, instruction modeling, test automation, and collaboration across the project.
June 2025
Activity
Loading activity data...
Quality Metrics
Correctness100.0%
Maintainability90.0%
Architecture90.0%
Performance90.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
ML
Technical Skills
ARM ArchitectureCo-simulationCompiler DesignCompiler DevelopmentFormal VerificationReverse Engineering
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline