DSA · Theory

Graph Representation

Theory

37/810

Graph Representation

Graph Representation is a DSA topic. In plain words you use it for bus routes in a city map. Don’t start with a slogan — start with that picture.

Smallest example: BFS queue / DFS stack. Type it, run it, and say what you see. If you can do that from memory, you know Graph Representation.

From the example next to this theory: Graph Representation — graphs are often stored as adjacency lists: vertex → list of (neighbor, weight).

Trap — no visited set → infinite loop. Fix that before you talk about advanced DSA.

Viva — what is Graph Representation? Then show BFS queue / DFS stack. Then name the trap.

Exam tip

What is Graph Representation? Show this: BFS queue / DFS stack. Trap: no visited set → infinite loop.

Example

# adjacency list
graph = {
    "A": [("B", 2), ("C", 5)],
    "B": [("A", 2), ("C", 1)],
    "C": [("A", 5), ("B", 1)],
}
for u, edges in graph.items():
    print(u, "->", edges)

Graph Representation — graphs are often stored as adjacency lists: vertex → list of (neighbor, weight).

Short notes

DefGraph Representation — bus routes in a city map.
RuleBFS queue / DFS stack
Trapno visited set → infinite loop
Usea city map

DSA · Theory

Graph Representation

← All stacks

Theory

37/810

Graph Representation

Graph Representation is a DSA topic. In plain words you use it for bus routes in a city map. Don’t start with a slogan — start with that picture.

Smallest example: BFS queue / DFS stack. Type it, run it, and say what you see. If you can do that from memory, you know Graph Representation.

From the example next to this theory: Graph Representation — graphs are often stored as adjacency lists: vertex → list of (neighbor, weight).

Trap — no visited set → infinite loop. Fix that before you talk about advanced DSA.

Viva — what is Graph Representation? Then show BFS queue / DFS stack. Then name the trap.

Exam tip

What is Graph Representation? Show this: BFS queue / DFS stack. Trap: no visited set → infinite loop.

Example

# adjacency list
graph = {
    "A": [("B", 2), ("C", 5)],
    "B": [("A", 2), ("C", 1)],
    "C": [("A", 5), ("B", 1)],
}
for u, edges in graph.items():
    print(u, "->", edges)

Graph Representation — graphs are often stored as adjacency lists: vertex → list of (neighbor, weight).

Short notes

DefGraph Representation — bus routes in a city map.
RuleBFS queue / DFS stack
Trapno visited set → infinite loop
Usea city map

Graph Representation

Example

Short notes

Questions

Graph Representation

Example

Short notes

Questions