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Question 1

¿Qué significa O(1)?

Answer 1

Tiempo constante. La operación siempre toma el mismo tiempo, sin importar el tamaño de la entrada.
Ej: return arr[0];

Question 2

¿Qué significa O(n)?

Answer 2

Tiempo lineal. El tiempo crece proporcional al tamaño de la entrada.
Ej: for (let i = 0; i < arr.length; i++)

Question 3

What does O(1) mean?

Answer 3

Constant time. The operation always takes the same amount of time, regardless of input size.
Example: return arr[0];

Question 4

What does O(n) mean?

Answer 4

Linear time. Time grows proportionally with input size.
Example: for (let i = 0; i < arr.length; i++)

Question 5

What does O(n²) mean?

Answer 5

Quadratic time. Two nested loops. Time increases rapidly with input size.
Example: for (i) { for (j) {} }

Question 6

What does O(log n) mean?

Answer 6

Logarithmic time. Cuts the problem in half each step.
Example: Binary search.

Question 7

What does O(n log n) mean?

Answer 7

Linearithmic time. Common in efficient sorting algorithms.
Example: Merge Sort, average-case Quick Sort.

Question 8

What does O(√n) mean?

Answer 8

Square root time. Often used in prime checking or divisor loops.
Example: for (i = 2; i <= sqrt(n); i++)

Question 9

What does O(2ⁿ) mean?

Answer 9

Exponential time. Very slow. Often from recursive branching.
Example: Naive recursive Fibonacci

Question 10

What does O(n!) mean?

Answer 10

Factorial time. Extremely slow. Seen in permutations and brute-force solutions.
Example: Generating all permutations of a list.

Question 11

What does O(kn) mean?

Answer 11

Linear time scaled by a second factor k. Seen in problems with nested input sizes.
Example: Processing n words of length k.

Question 12

What does O(V + E) mean?

Answer 12

Graph algorithms. V = vertices, E = edges. Total time scales with graph size.
Example: BFS or DFS traversal.

Question 13

What does O(E log V) mean?

Answer 13

Graph algorithms using priority queues (heaps).
Example: Dijkstra’s algorithm with a min-heap.