
Pablo García-Fernández contributed to the open-quantum-safe/liboqs project by building and refining automated benchmarking and cryptographic integration workflows. He implemented continuous and later weekly benchmarking infrastructure using Python scripting and GitHub Actions, enabling reliable performance tracking for KEM and digital signature algorithms. His work included tuning alert thresholds to reduce noise and updating CI/CD pipelines and documentation to support evolving workflows. Pablo also addressed OpenSSL integration issues in C, improving test observability and algorithm version traceability. These efforts enhanced the project’s reliability, streamlined performance monitoring, and provided actionable data for optimization, demonstrating depth in CI/CD, benchmarking, and workflow automation.

September 2025 monthly summary for open-quantum-safe/liboqs focusing on key accomplishments and impact. Key features delivered: Implemented a Weekly Performance Benchmarking Schedule by shifting continuous benchmarking to a weekly cadence; updated CI configuration and documentation to reflect the new workflow. Major bugs fixed: None reported for Sep 2025. Overall impact and accomplishments: Provides consistent performance signals aligned with release planning, reduces noise in benchmarking results, and streamlines CI maintenance, enabling faster, more reliable performance-driven decisions. Technologies/skills demonstrated: CI/CD configuration and maintenance, benchmarking automation, Git-based traceability, documentation discipline, and cross-team collaboration.
September 2025 monthly summary for open-quantum-safe/liboqs focusing on key accomplishments and impact. Key features delivered: Implemented a Weekly Performance Benchmarking Schedule by shifting continuous benchmarking to a weekly cadence; updated CI configuration and documentation to reflect the new workflow. Major bugs fixed: None reported for Sep 2025. Overall impact and accomplishments: Provides consistent performance signals aligned with release planning, reduces noise in benchmarking results, and streamlines CI maintenance, enabling faster, more reliable performance-driven decisions. Technologies/skills demonstrated: CI/CD configuration and maintenance, benchmarking automation, Git-based traceability, documentation discipline, and cross-team collaboration.
In June 2025, delivered automated benchmarking infrastructure for KEM and digital signatures in open-quantum-safe/liboqs, enabling continuous performance visibility, standardized result formatting, and improved alerting. The work reduces mean time to detect regressions and provides actionable data for optimization, aligning with business goals of reliability and performance at scale. Key commits were made to implement continuous benchmarking and tune alerts: d745d35938d17e666ffa88673523fd4c4399d326 and a56b796271ad41c3152ea19f8149281431d86098.
In June 2025, delivered automated benchmarking infrastructure for KEM and digital signatures in open-quantum-safe/liboqs, enabling continuous performance visibility, standardized result formatting, and improved alerting. The work reduces mean time to detect regressions and provides actionable data for optimization, aligning with business goals of reliability and performance at scale. Key commits were made to implement continuous benchmarking and tune alerts: d745d35938d17e666ffa88673523fd4c4399d326 and a56b796271ad41c3152ea19f8149281431d86098.
February 2025 monthly delivery for liboqs focused on stabilizing cryptographic integration and improving test observability. Delivered an OpenSSL integration bug fix with dependency updates and enhanced test reporting for KEMs and signature algorithms. These efforts improve production reliability, reduce debugging time, and strengthen verifiability of algorithm versions across tests.
February 2025 monthly delivery for liboqs focused on stabilizing cryptographic integration and improving test observability. Delivered an OpenSSL integration bug fix with dependency updates and enhanced test reporting for KEMs and signature algorithms. These efforts improve production reliability, reduce debugging time, and strengthen verifiability of algorithm versions across tests.
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