Q1easy
What is "Space-Time Trade-off" in algorithmic optimization?
Back to Problem Solving & Analytical Skills
22 Questions Total
Complexity & Efficiency Awareness MCQs
Topic-wise practice questions for Problem Solving & Analytical Skills. Test your knowledge, check solutions on demand, and pace your preparation.
Zero-leak answer engine • Rate-limited explanations
Practice in Timed ModeQ2medium
You have three algorithms for the same task. Algorithm A is O(N²), Algorithm B is O(N log N), and Algorithm C is O(2^N). For an input size of N = 100, which is the most efficient?
Q3hard
(Code-Analysis) What is the space complexity of a recursive function that calls itself N times (e.g., recursive factorial)?
Q4medium
In Big-O notation, which term is dominant and kept for f(n) = 5n³ +
2n² + 100 log n + 500?
Q5hard
A developer is building a search feature for a list of 100,000 items. The list is not sorted. Which complexity will they face for a single search?
Q6hard
An algorithm is O(N!). This complexity is most commonly associated with which type of problem?
Q7easy
What does Big-O notation strictly represent in algorithmic analysis?
Q8hard
(Code-Analysis) What is the time complexity of the following code snippet?
for (int i = 0; i < N; i++) {
for (int j = 0; j < N; j++) {
print(i, j);
}
}
Q9easy
What does "Big-Omega (Ω)" notation represent?
Q10medium
How many times will the "action" be performed in this loop?
for (int i = 0; i < N; i++) {
for (int j = i; j < N; j++) {
// action
}
}