Data Structures MCQs with Answers
Practice important Data Structures MCQs with answers and explanations.
Multiple Choice Questions
Q631: What is a key characteristic of a skip list's structure?
- A: Array of next pointers
- B: Array of previous pointers
- C: Doubly linked nodes
- D: Quadruple linked nodes
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A
Q632: How does a TowerNode in a skip list manage multiple pointers?
- A: Uses an array of pointers
- B: Uses a single linked list
- C: Uses a doubly linked list
- D: Uses a multi-level array
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A
Q633: What does MAXLEVEL specify in the context of a skip list?
- A: The maximum number of data elements
- B: The maximum number of next pointers
- C: The maximum height of the skip list
- D: The maximum number of skip list levels
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C
Q634: What is a major advantage of using a Quad Node compared to a TowerNode?
- A: It does not require an array of pointers
- B: It requires fewer memory allocations
- C: It allows for faster insertions
- D: It simplifies the pointer management
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A
Q635: In a skip list, how is the insertion level of a node determined?
- A: By flipping a coin
- B: By generating a random number
- C: By calculating the node's data value
- D: By counting the number of nodes
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A
Q636: What is the expected time complexity for search operations in a skip list?
- A: O(1)
- B: O(n)
- C: O(log n)
- D: O(n^2)
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C
Q637: How does hashing improve the performance of data retrieval?
- A: By storing data in sorted order
- B: By using a hash function to map keys to indices
- C: By using a balanced tree structure
- D: By allocating memory dynamically
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B
Q638: What is the primary role of a hash function in hashing?
- A: To generate unique keys for each data entry
- B: To map a key to a specific index in the array
- C: To sort the data entries
- D: To encrypt the data entries
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B
Q639: What is the expected space complexity of a skip list with n items?
- A: O(n)
- B: O(n^2)
- C: O(log n)
- D: O(n log n)
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A
Q640: Which of the following hash functions is used in the provided C++ example?
- A: sum = sum + s[i];
- B: sum = s[i] * i;
- C: sum = s[i] ^ i;
- D: sum = s[i] + i * TABLESIZE;
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A