Data Structures MCQs

Weighted Graph is a graph whose edges or vertices carry numeric costs or values.
This description distinguishes it from the other choices.

Weighted Graph is commonly used for shortest-path and network optimization problems.
Its design supports this task efficiently or naturally.

The defining property is that path quality can depend on the sum of weights.
The other statements describe different structures or concepts.

Weighted Graph fits because it supports shortest-path and network optimization problems and path quality can depend on the sum of weights.
Both clues point to this choice.

Adjacency Matrix is a square matrix indicating which vertex pairs are connected.
This description distinguishes it from the other choices.

Adjacency Matrix is commonly used for dense graphs and constant-time edge-existence tests.
Its design supports this task efficiently or naturally.

The defining property is that its space usage is quadratic in the number of vertices.
The other statements describe different structures or concepts.

Adjacency Matrix fits because it supports dense graphs and constant-time edge-existence tests and its space usage is quadratic in the number of vertices.
Both clues point to this choice.

Directed Graph fits because it supports modeling one-way relationships and an edge from u to v need not imply an edge from v to u.
Both clues point to this choice.

Undirected Graph is a graph whose edges have no direction.
This description distinguishes it from the other choices.

Undirected Graph is commonly used for modeling symmetric relationships.
Its design supports this task efficiently or naturally.

The defining property is that each edge connects two vertices bidirectionally.
The other statements describe different structures or concepts.