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Algorithmic Thinking

Topic in Problem Solving & Analytical Skills

210 total MCQsShowing 30 with explanations10 Easy10 Medium10 Hard
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About This Topic

Algorithmic thinking is the ability to express a solution as precise, repeatable steps and pick a strategy that is correct and efficient. MCQs compare major design paradigms: brute force, greedy choice, divide and conquer, dynamic programming with memoization or tabulation, and backtracking. You may be asked to estimate how an O(n log n) or O(n^2) algorithm scales when the input doubles, or to identify which approach fits problems like coin change, knapsack, shortest paths and scheduling. Advanced items explain how A* combines path cost g(n) with a heuristic h(n), and how branch and bound prunes an optimization search space.

Below are 30 practice questions from a pool of 210 Algorithmic Thinking MCQs, one of 16 topics in Problem Solving & Analytical Skills. Each shows the correct answer with an explanation; when you are ready, take a timed quiz to test recall under exam conditions.

Practice Questions

Each question below shows the correct answer with a full explanation. Use these to build conceptual understanding before attempting a timed quiz.

Algorithmic ThinkingEasy

Q1. What is algorithmic thinking?

  1. A.Memorizing algorithms from textbooks
  2. B.Avoiding any structured approach
  3. C.Defining clear steps to solve problems✓ Correct
  4. D.Thinking about hardware components

Explanation

Clear step-by-step solutions.

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Algorithmic ThinkingEasy

Q2. Simplest search?

  1. A.Hash lookup
  2. B.Jump search
  3. C.Linear search✓ Correct
  4. D.Binary search

Explanation

Checks each element sequentially.

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Algorithmic ThinkingEasy

Q3. Binary search requires?

  1. A.Only integer type values
  2. B.An odd length data array
  3. C.A sorted list of elements✓ Correct
  4. D.An empty list as input

Explanation

Sorted data required.

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Algorithmic ThinkingEasy

Q4. Bubble sort idea?

  1. A.Insert each into a sorted tree
  2. B.Select the minimum each time
  3. C.Swap adjacent wrong-order elements✓ Correct
  4. D.Divide the array in half first

Explanation

Adjacent element swapping.

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Algorithmic ThinkingEasy

Q5. What is sorting?

  1. A.Copying data to a new place
  2. B.Deleting unwanted elements
  3. C.Searching for an element
  4. D.Arranging in a specific order✓ Correct

Explanation

Arranging in order.

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Algorithmic ThinkingEasy

Q6. Linear search worst case?

  1. A.O(n)✓ Correct
  2. B.O(1)
  3. C.O(log n)
  4. D.O(n^2)

Explanation

O(n) is the correct answer to this question.

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Algorithmic ThinkingEasy

Q7. What is greedy?

  1. A.Best choice at each step locally✓ Correct
  2. B.Always using recursive functions
  3. C.Using lots of memory resources
  4. D.Running very slowly on purpose

Explanation

Locally optimal choices.

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Algorithmic ThinkingEasy

Q8. What is recursive algorithm?

  1. A.Calls itself with smaller instances✓ Correct
  2. B.An algorithm without any loops
  3. C.An algorithm that runs only once
  4. D.An algorithm that never repeats

Explanation

Self-calling with smaller inputs.

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Algorithmic ThinkingEasy

Q9. BFS uses?

  1. A.Array structure
  2. B.Stack structure
  3. C.Hash table
  4. D.Queue structure✓ Correct

Explanation

Queue for level-by-level.

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Algorithmic ThinkingEasy

Q10. DFS uses?

  1. A.Heap structure
  2. B.Hash table lookup
  3. C.Queue structure
  4. D.Stack or recursion✓ Correct

Explanation

Stack/recursion for depth-first.

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Algorithmic ThinkingMedium

Q11. Binary search complexity?

  1. A.O(1)
  2. B.O(log n)✓ Correct
  3. C.O(n)
  4. D.O(n^2)

Explanation

O(log n) is the correct answer to this question.

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Algorithmic ThinkingMedium

Q12. Merge sort complexity?

  1. A.O(n^2)
  2. B.O(n log n)✓ Correct
  3. C.O(n)
  4. D.O(log n)

Explanation

Always O(n log n).

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Algorithmic ThinkingMedium

Q13. Quicksort worst case?

  1. A.O(n log n)
  2. B.O(n^2)✓ Correct
  3. C.O(log n)
  4. D.O(n)

Explanation

O(n^2) with bad pivots.

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Algorithmic ThinkingMedium

Q14. When greedy over DP?

  1. A.Always use greedy by default
  2. B.When the problem is NP-hard
  3. C.Never use greedy over DP
  4. D.Greedy-choice property plus optimal substructure✓ Correct

Explanation

When local optimal = global optimal.

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Algorithmic ThinkingMedium

Q15. What is backtracking?

  1. A.A data compression approach
  2. B.Never going back on choices
  3. C.A sorting algorithm technique
  4. D.Try solutions, undo failed ones✓ Correct

Explanation

Abandons failed paths.

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Algorithmic ThinkingMedium

Q16. N-Queens uses?

  1. A.Greedy approach
  2. B.Backtracking method✓ Correct
  3. C.Linear search scan
  4. D.Dynamic programming

Explanation

Classic backtracking problem.

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Algorithmic ThinkingMedium

Q17. Dijkstra's is for?

  1. A.String pattern matching
  2. B.Balancing binary trees
  3. C.Shortest paths, non-negative weights✓ Correct
  4. D.Sorting array elements

Explanation

Single-source shortest paths.

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Algorithmic ThinkingMedium

Q18. Hash function purpose?

  1. A.Compressing files for storage
  2. B.Mapping keys to indices for lookup✓ Correct
  3. C.Encrypting sensitive user data
  4. D.Sorting data in an array

Explanation

Average O(1) lookups.

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Algorithmic ThinkingMedium

Q19. What is stable sort?

  1. A.Maintains equal elements relative order✓ Correct
  2. B.A sort using constant space only
  3. C.A sort that never crashes at all
  4. D.The fastest sorting algorithm known

Explanation

Preserves relative order.

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Algorithmic ThinkingMedium

Q20. Which sort is not comparison-based?

  1. A.Heap sort
  2. B.Counting sort✓ Correct
  3. C.Quick sort
  4. D.Merge sort

Explanation

Counting sort: no comparisons.

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Algorithmic ThinkingHard

Q21. Comparison sort lower bound?

  1. A.O(log n)
  2. B.O(n log n)✓ Correct
  3. C.O(n)
  4. D.O(n^2)

Explanation

Omega(n log n).

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Algorithmic ThinkingHard

Q22. What is approximation algorithm?

  1. A.Produces random unpredictable results
  2. B.Always gives exact solutions
  3. C.Near-optimal with provable guarantees✓ Correct
  4. D.Tries all solutions by brute force

Explanation

Provable quality bounds.

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Algorithmic ThinkingHard

Q23. What is A*?

  1. A.A string matching technique
  2. B.A linear search method only
  3. C.Best-first search using heuristics✓ Correct
  4. D.A sorting algorithm for arrays

Explanation

Combines g(n)+h(n) for optimal pathfinding.

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Algorithmic ThinkingHard

Q24. What is branch and bound?

  1. A.A tree data structure type
  2. B.A sorting algorithm approach
  3. C.A compression technique used
  4. D.Prunes branches worse than best✓ Correct

Explanation

Prunes unpromising branches.

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Algorithmic ThinkingHard

Q25. Floyd-Warshall complexity?

  1. A.O(V^2)
  2. B.O(V^3)✓ Correct
  3. C.O(V*E)
  4. D.O(E log V)

Explanation

Three nested loops: O(V^3).

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Algorithmic ThinkingHard

Q26. What is randomized algorithm?

  1. A.An algorithm with no clear structure
  2. B.An algorithm that has bugs in it
  3. C.Uses random choices for performance✓ Correct
  4. D.An algorithm that is always wrong

Explanation

Random choices for performance.

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Algorithmic ThinkingHard

Q27. Las Vegas vs Monte Carlo?

  1. A.LV: always correct; MC: may err sometimes✓ Correct
  2. B.Monte Carlo is always correct output
  3. C.They are exactly the same algorithm
  4. D.Las Vegas is always faster in practice

Explanation

LV correct; MC may err.

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Algorithmic ThinkingHard

Q28. Amortized O(1) dynamic array?

  1. A.The array never resizes at all
  2. B.Every single operation is O(1)
  3. C.Some O(n) resizes, average O(1)✓ Correct
  4. D.All operations take O(log n)

Explanation

Doubling gives amortized O(1).

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Algorithmic ThinkingHard

Q29. Kruskal's key idea?

  1. A.Use DFS for tree construction
  2. B.Start from a single vertex first
  3. C.Sort edges, add non-cycle-forming✓ Correct
  4. D.Use BFS for tree construction

Explanation

Greedily adds lightest safe edges.

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Algorithmic ThinkingHard

Q30. KMP solves?

  1. A.Sorting array elements fast
  2. B.Pattern matching in O(n+m)✓ Correct
  3. C.Matrix multiplication task
  4. D.Graph traversal and search

Explanation

O(n+m) pattern matching.

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