mit-pdos/perennial
Aug 2025 – Aug 2025
1 Month active
Languages Used
CoqGo
Technical Skills
Algorithm OptimizationAlgorithmsData StructuresFormal VerificationFunctional ProgrammingLow-level Programming
Sanjit Bhat
PROFILE
Sanjit Bhat
Sanjit Bhat developed and stabilized the deterministic Merkle Put core in the mit-pdos/perennial repository, focusing on enabling reproducible state updates and simplifying formal verification. He refactored the pure_put logic to clarify deterministic paths and reduce recursion, laying a foundation for improved reliability and maintainability. By introducing Gallina translations for key functions, Sanjit streamlined proof construction and verification in Coq, supporting safer production deployments. He also addressed a subtle bug in the merkle_proof theory, enhancing proof accuracy. His work demonstrated depth in algorithm optimization, formal verification, and low-level programming, resulting in more robust and verifiable Merkle tree operations.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
6Total
Bugs
1
Commits
6
Features
1
Lines of code
274
Activity Months1
Your Network
16 people
Work History
August 2025
6 Commits • 1 Features
Aug 1, 2025In August 2025, delivered deterministic Merkle Put core and stabilized the proof workflow in mit-pdos/perennial, enabling deterministic state updates and easier proof construction and verification. Fixed a typo in merkle_proof theory affecting pure_put, improving proof reliability. These changes enhance correctness, reproducibility, and maintainability, laying groundwork for deterministic guarantees and safer production deployments.
6 Commits • 1 Features
Aug 1, 2025In August 2025, delivered deterministic Merkle Put core and stabilized the proof workflow in mit-pdos/perennial, enabling deterministic state updates and easier proof construction and verification. Fixed a typo in merkle_proof theory affecting pure_put, improving proof reliability. These changes enhance correctness, reproducibility, and maintainability, laying groundwork for deterministic guarantees and safer production deployments.
August 2025
Activity
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Quality Metrics
Correctness85.0%
Maintainability83.4%
Architecture85.0%
Performance71.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
CoqGo
Technical Skills
Algorithm OptimizationAlgorithmsData StructuresFormal VerificationFunctional ProgrammingLow-level ProgrammingMerkle TreesProof Engineering
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