distributed-algorithms

What problem does it solve?

Lynch's body of work on distributed algorithms provides rigorous models, impossibility results, and canonical problem solutions that guide robust system design.

Core Features & Use Cases

• Canonical problems and patterns: leader election, BFS/spanning trees, shortest paths, MST, consensus, mutual exclusion, and global snapshots
• Proof methods and design patterns: invariants, simulation, indistinguishability arguments, timing-aware proofs, and composition theorems
• Practical model escape routes: randomization, failure detectors, partial synchrony, authentication, and authenticated Byzantine approaches
• Model-driven engineering: applying to distributed systems design and teaching

Quick Start

Begin with FLP impossibility, then map models to problems, and review canonical algorithm rounds and bounds to apply them to your design.