DSA · Theory

Searching in Graph Data Structure

Theory

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Searching in Graph Data Structure

Searching in Graph Data Structure 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 Searching in Graph Data Structure.

From the example next to this theory: Searching in Graph Data Structure — 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 Searching in Graph Data Structure? Then show BFS queue / DFS stack. Then name the trap.

Exam tip

What is Searching in Graph Data Structure? 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)

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

Short notes

DefSearching in Graph Data Structure — bus routes in a city map.
RuleBFS queue / DFS stack
Trapno visited set → infinite loop
Usea city map

DSA · Theory

Searching in Graph Data Structure

← All stacks

Theory

810/810

Searching in Graph Data Structure

Searching in Graph Data Structure 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 Searching in Graph Data Structure.

From the example next to this theory: Searching in Graph Data Structure — 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 Searching in Graph Data Structure? Then show BFS queue / DFS stack. Then name the trap.

Exam tip

What is Searching in Graph Data Structure? 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)

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

Short notes

DefSearching in Graph Data Structure — bus routes in a city map.
RuleBFS queue / DFS stack
Trapno visited set → infinite loop
Usea city map

Searching in Graph Data Structure

Example

Short notes

Questions

Searching in Graph Data Structure

Example

Short notes

Questions