Directed Acyclic Graph
A Directed Acyclic Graph (DAG) is a finite directed graph with no directed cycles, meaning it consists of vertices and directed edges where no sequence of edges forms a closed loop. It is a fundamental data structure in computer science used to model dependencies, precedence constraints, and topological ordering. DAGs are widely applied in scheduling, data processing, version control systems, and blockchain technologies.
Developers should learn DAGs when working on systems that require dependency resolution, such as task scheduling in build tools (e.g., Make, Gradle), data pipeline orchestration (e.g., Apache Airflow), or distributed ledger implementations (e.g., IOTA, Hedera Hashgraph). They are essential for ensuring efficient, non-cyclic workflows and are a core concept in graph theory with applications in machine learning for Bayesian networks and compiler design for control flow graphs.