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Directed Acyclic Graph

A Directed Acyclic Graph (DAG) is a finite directed graph with no directed cycles, meaning it consists of vertices and edges where each edge has a direction and there is no way to start at a vertex and follow a sequence of edges that loops back to it. It is a fundamental data structure in computer science used to model dependencies, precedence constraints, and workflows where tasks must be executed in a specific order without circular dependencies. DAGs are widely applied in areas like task scheduling, data processing pipelines, version control systems, and blockchain technologies.

Also known as: DAG, Directed Acyclic Graph, Acyclic Digraph, Non-cyclic Directed Graph, Dependency Graph
🧊Why learn Directed Acyclic Graph?

Developers should learn about DAGs when designing systems that involve dependency management, such as build tools (e.g., Make, Gradle), workflow orchestration (e.g., Apache Airflow), or data lineage in ETL processes, as they provide an efficient way to represent and traverse hierarchical or sequential relationships. They are also crucial in blockchain implementations like IOTA or Hedera Hashgraph, where DAGs enable scalable and fast consensus mechanisms without traditional blocks, making them valuable for distributed systems and decentralized applications.

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