DSA · Theory

Difference between Tree edge and Back edge in a graph in the Data Structure

Theory

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Difference between Tree edge and Back edge in a graph in the Data Structure

Difference between Tree edge and Back edge in a graph in the Data Structure is a DSA topic. In plain words you use it for folder on disk in a file explorer. Don’t start with a slogan — start with that picture.

Smallest example: left < root < right. Type it, run it, and say what you see. If you can do that from memory, you know Difference between Tree edge and Back edge in a graph in the Data Structure.

From the example next to this theory: Difference between Tree edge and Back edge in a graph in the Data Structure — graphs are often stored as adjacency lists: vertex → list of (neighbor, weight).

Trap — unbalanced BST becoming a list. Fix that before you talk about advanced DSA.

Viva: what is Difference between Tree edge and Back edge in a graph in the Data Structure? Then show left < root < right. Then name the trap.

Exam tip

What is Difference between Tree edge and Back edge in a graph in the Data Structure? Show this: left < root < right. Trap: unbalanced BST becoming a list.

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)

Difference between Tree edge and Back edge in a graph in the Data Structure — graphs are often stored as adjacency lists: vertex → list of (neighbor, weight).

Short notes

DefDifference between Tree edge and Back edge in a graph in the Data Structure — folder on disk in a file explorer.
Ruleleft < root < right
Trapunbalanced BST becoming a list
Usea file explorer

DSA · Theory

Difference between Tree edge and Back edge in a graph in the Data Structure

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Theory

783/810

Difference between Tree edge and Back edge in a graph in the Data Structure

Smallest example: left < root < right. Type it, run it, and say what you see. If you can do that from memory, you know Difference between Tree edge and Back edge in a graph in the Data Structure.

Trap — unbalanced BST becoming a list. Fix that before you talk about advanced DSA.

Viva: what is Difference between Tree edge and Back edge in a graph in the Data Structure? Then show left < root < right. Then name the trap.

Exam tip

What is Difference between Tree edge and Back edge in a graph in the Data Structure? Show this: left < root < right. Trap: unbalanced BST becoming a list.

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)

Difference between Tree edge and Back edge in a graph in the Data Structure — graphs are often stored as adjacency lists: vertex → list of (neighbor, weight).

Short notes

DefDifference between Tree edge and Back edge in a graph in the Data Structure — folder on disk in a file explorer.
Ruleleft < root < right
Trapunbalanced BST becoming a list
Usea file explorer

Difference between Tree edge and Back edge in a graph in the Data Structure

Example

Short notes

Questions

Difference between Tree edge and Back edge in a graph in the Data Structure

Example

Short notes

Questions