Reducing graph complexity using Go and transitive reduction

Click for: original source

Directed acyclic graphs (DAGs) serve a wide variety of applications in computer science, biology, sociology, and other fields that involve complex networks. While these graphs often contain a large number of edges, some of the edges might be redundant, making computations unnecessarily expensive and the graph structure harder to understand. By Dominik Braun.

This article demonstrates how a DAG can be built in Go using the graph library and describes the algorithm to remove these redundant edges in detail. Further it explains:

  • Transitive reduction
  • Building the DAG
  • Computing the transitive reduction
  • Implementing the algorithm
  • Using transitive reduction in your application

Adding numerous edges to a DAG can make the graph unnecessarily complex. However, these graphs can be simplified using a technique called transitive reduction. Good read!

[Read More]

Tags apis app-development performance golang database