What are the best data structures for graph search?

What are the best data structures for graph search?

The best data structures for graph search include adjacency lists, adjacency matrices, and edge lists. Each has its own advantages depending on the graph's density and the operations you need to perform.

Can you explain when to use an adjacency list over an adjacency matrix?

Sure! Use an adjacency list for sparse graphs as it saves space and allows for efficient traversal. An adjacency matrix is better for dense graphs where you need quick access to check if an edge exists.

What about edge lists? When should I use them?

Edge lists are useful when you need to store a simple list of edges, especially in algorithms that require iterating over edges, like Kruskal's algorithm for minimum spanning trees.

Are there any specific algorithms that work better with certain data structures?

Yes, for example, Dijkstra's algorithm works well with adjacency lists when implemented with a priority queue, while Floyd-Warshall is more suited for adjacency matrices.