Data Structures & Algorithms

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Typical Problems - Problem Set Sorting Algorithms: Quick, Merge, Heap - Typical Problems - Real World Applications Stacks and Queues Stacks and Queues - Advanced Concepts Stacks and Queues - Applications Stacks and Queues - Applications - Advanced Concepts Stacks and Queues - Applications - Applications Stacks and Queues - Applications - Case Studies Stacks and Queues - Applications - Competitive Exam Level Stacks and Queues - Applications - Higher Difficulty Problems Stacks and Queues - Applications - Numerical Applications Stacks and Queues - Applications - Problem Set Stacks and Queues - Applications - Real World Applications Stacks and Queues - Case Studies Stacks and Queues - Competitive Exam Level Stacks and Queues - Complexity Analysis Stacks and Queues - Complexity Analysis - Advanced Concepts Stacks and Queues - Complexity Analysis - Applications Stacks and Queues - Complexity Analysis - Case Studies Stacks and Queues - Complexity Analysis - Competitive Exam Level Stacks and Queues - Complexity Analysis - Higher Difficulty Problems Stacks and Queues - Complexity Analysis - Numerical Applications Stacks and Queues - Complexity Analysis - Problem Set Stacks and Queues - Complexity Analysis - Real World Applications Stacks and Queues - Higher Difficulty Problems Stacks and Queues - Implementations in C++ Stacks and Queues - Implementations in C++ - Advanced Concepts Stacks and Queues - Implementations in C++ - Applications Stacks and Queues - Implementations in C++ - Case Studies Stacks and Queues - Implementations in C++ - Competitive Exam Level Stacks and Queues - Implementations in C++ - Higher Difficulty Problems Stacks and Queues - Implementations in C++ - Numerical Applications Stacks and Queues - Implementations in C++ - Problem Set Stacks and Queues - Implementations in C++ - Real World Applications Stacks and Queues - Implementations in Python Stacks and Queues - Implementations in Python - Advanced Concepts Stacks and Queues - Implementations in Python - Applications Stacks and Queues - Implementations in Python - Case Studies Stacks and Queues - Implementations in Python - Competitive Exam Level Stacks and Queues - Implementations in Python - Higher Difficulty Problems Stacks and Queues - Implementations in Python - Numerical Applications Stacks and Queues - Implementations in Python - Problem Set Stacks and Queues - Implementations in Python - Real World Applications Stacks and Queues - Numerical Applications Stacks and Queues - Problem Set Stacks and Queues - Real World Applications Stacks and Queues - Typical Problems Stacks and Queues - Typical Problems - Advanced Concepts Stacks and Queues - Typical Problems - Applications Stacks and Queues - Typical Problems - Case Studies Stacks and Queues - Typical Problems - Competitive Exam Level Stacks and Queues - Typical Problems - Higher Difficulty Problems Stacks and Queues - Typical Problems - Numerical Applications Stacks and Queues - Typical Problems - Problem Set Stacks and Queues - Typical Problems - Real World Applications Trees and Graphs Trees and Graphs - Advanced Concepts Trees and Graphs - Applications Trees and Graphs - Applications - Advanced Concepts Trees and Graphs - Applications - Applications Trees and Graphs - Applications - Case Studies Trees and Graphs - Applications - Competitive Exam Level Trees and Graphs - Applications - Higher Difficulty Problems Trees and Graphs - Applications - Numerical Applications Trees and Graphs - Applications - Problem Set Trees and Graphs - Applications - Real World Applications Trees and Graphs - Case Studies Trees and Graphs - Competitive Exam Level Trees and Graphs - Complexity Analysis Trees and Graphs - Complexity Analysis - Advanced Concepts Trees and Graphs - Complexity Analysis - Applications Trees and Graphs - Complexity Analysis - Case Studies Trees and Graphs - Complexity Analysis - Competitive Exam Level Trees and Graphs - Complexity Analysis - Higher Difficulty Problems Trees and Graphs - Complexity Analysis - Numerical Applications Trees and Graphs - Complexity Analysis - Problem Set Trees and Graphs - Complexity Analysis - Real World Applications Trees and Graphs - Higher Difficulty Problems Trees and Graphs - Implementations in C++ Trees and Graphs - Implementations in C++ - Advanced Concepts Trees and Graphs - Implementations in C++ - Applications Trees and Graphs - Implementations in C++ - Case Studies Trees and Graphs - Implementations in C++ - Competitive Exam Level Trees and Graphs - Implementations in C++ - Higher Difficulty Problems Trees and Graphs - Implementations in C++ - Numerical Applications Trees and Graphs - Implementations in C++ - Problem Set Trees and Graphs - Implementations in C++ - Real World Applications Trees and Graphs - Implementations in Python Trees and Graphs - Implementations in Python - Advanced Concepts Trees and Graphs - Implementations in Python - Applications Trees and Graphs - Implementations in Python - Case Studies Trees and Graphs - Implementations in Python - Competitive Exam Level Trees and Graphs - Implementations in Python - Higher Difficulty Problems Trees and Graphs - Implementations in Python - Numerical Applications Trees and Graphs - Implementations in Python - Problem Set Trees and Graphs - Implementations in Python - Real World Applications Trees and Graphs - Numerical Applications Trees and Graphs - Problem Set Trees and Graphs - Real World Applications Trees and Graphs - Typical Problems Trees and Graphs - Typical Problems - Advanced Concepts Trees and Graphs - Typical Problems - Applications Trees and Graphs - Typical Problems - Case Studies Trees and Graphs - Typical Problems - Competitive Exam Level Trees and Graphs - Typical Problems - Higher Difficulty Problems Trees and Graphs - Typical Problems - Numerical Applications Trees and Graphs - Typical Problems - Problem Set Trees and Graphs - Typical Problems - Real World Applications
Q. Which of the following is true about a complete binary tree?
  • A. All levels are fully filled except possibly the last level.
  • B. All nodes have two children.
  • C. It is always balanced.
  • D. It has a maximum height of log n.
Q. Which of the following is true about a doubly linked list?
  • A. Each node has one pointer
  • B. Nodes can be traversed in both directions
  • C. It uses less memory than a singly linked list
  • D. It is always sorted
Q. Which of the following is true about a queue?
  • A. LIFO structure
  • B. FIFO structure
  • C. Random access
  • D. None of the above
Q. Which of the following is true about a stack?
  • A. Elements can be accessed in any order
  • B. Elements are removed in FIFO order
  • C. Elements are removed in LIFO order
  • D. None of the above
Q. Which of the following is true about arrays?
  • A. They can grow dynamically
  • B. They allow random access
  • C. They are always faster than linked lists
  • D. They require more memory than linked lists
Q. Which of the following is true about AVL trees compared to Red-Black trees?
  • A. AVL trees are faster for lookup operations.
  • B. Red-Black trees are faster for lookup operations.
  • C. Both have the same performance.
  • D. AVL trees are easier to implement.
Q. Which of the following is true about BFS?
  • A. It uses a stack
  • B. It finds the shortest path in unweighted graphs
  • C. It is faster than DFS
  • D. It cannot be implemented recursively
Q. Which of the following is true about DFS?
  • A. It can be implemented using recursion
  • B. It always finds the shortest path
  • C. It uses a queue
  • D. It is not suitable for cyclic graphs
Q. Which of the following is true about linked lists compared to arrays?
  • A. Linked lists have a fixed size
  • B. Arrays allow dynamic resizing
  • C. Linked lists allow efficient insertions/deletions
  • D. Arrays are more memory efficient
Q. Which of the following is true about Quick Sort?
  • A. It is always faster than Merge Sort
  • B. It is not in-place
  • C. It can be implemented using recursion
  • D. It is stable
Q. Which of the following is true about Red-Black Trees?
  • A. They are always perfectly balanced
  • B. They can have a maximum height of 2 log n
  • C. They guarantee O(log n) time for all operations
  • D. They require more memory than AVL trees
Q. Which of the following is true about the balancing of AVL trees?
  • A. They require rotations to maintain balance after insertions and deletions.
  • B. They do not require any balancing.
  • C. They can only be balanced by deleting nodes.
  • D. They are always balanced after every insertion.
Q. Which of the following is true about the height of a binary tree with n nodes?
  • A. Height = n
  • B. Height = log n
  • C. Height <= n
  • D. Height = n/2
Q. Which of the following is true about the height of a binary tree?
  • A. Height is the number of nodes in the longest path from root to leaf
  • B. Height is the number of edges in the longest path from root to leaf
  • C. Height is always equal to the number of levels in the tree
  • D. Height can be negative
Q. Which of the following is true about the height of a Red-Black tree?
  • A. It can be at most twice the height of an AVL tree.
  • B. It is always equal to the height of a binary search tree.
  • C. It is always less than or equal to log(n).
  • D. It can be greater than the height of an AVL tree.
Q. Which of the following is true about the inorder traversal of a binary search tree?
  • A. It visits nodes in random order.
  • B. It visits nodes in descending order.
  • C. It visits nodes in ascending order.
  • D. It visits only the leaf nodes.
Q. Which of the following is true about the level-order traversal of a binary tree?
  • A. It is depth-first
  • B. It uses a stack
  • C. It visits nodes level by level
  • D. It is faster than in-order traversal
Q. Which of the following is true about the performance of AVL trees?
  • A. Faster than Red-Black Trees for all operations
  • B. Slower than Red-Black Trees for all operations
  • C. Faster for search operations but slower for insertions
  • D. Slower for search operations but faster for insertions
Q. Which of the following modifications can be made to binary search to find the first occurrence of a target value?
  • A. Change the comparison operator
  • B. Use a different data structure
  • C. Modify the mid-point calculation
  • D. Continue searching left after finding the target
Q. Which of the following operations can be performed in constant time on an array?
  • A. Insertion at end
  • B. Deletion from beginning
  • C. Accessing an element
  • D. Insertion at beginning
Q. Which of the following operations can be performed in O(1) time on a linked list?
  • A. Insertion at the end
  • B. Deletion from the beginning
  • C. Searching for an element
  • D. Traversal
Q. Which of the following operations can be performed in O(1) time on a stack?
  • A. Push
  • B. Pop
  • C. Peek
  • D. All of the above
Q. Which of the following operations can cause a violation of the AVL tree property?
  • A. Insertion of a node.
  • B. Deletion of a node.
  • C. Both insertion and deletion.
  • D. Traversal of the tree.
Q. Which of the following operations can cause an imbalance in an AVL tree?
  • A. Insertion
  • B. Deletion
  • C. Both Insertion and Deletion
  • D. Traversal
Q. Which of the following operations has a time complexity of O(1) in a stack?
  • A. Push
  • B. Pop
  • C. Peek
  • D. All of the above
Q. Which of the following operations has a time complexity of O(n) in a linked list?
  • A. Accessing an element
  • B. Inserting at the end
  • C. Deleting a node
  • D. Searching for a value
Q. Which of the following operations has a time complexity of O(n) in a singly linked list?
  • A. Insertion at head
  • B. Insertion at tail
  • C. Deletion at head
  • D. Accessing an element by index
Q. Which of the following operations has a time complexity of O(n) in a stack?
  • A. Push
  • B. Pop
  • C. Peek
  • D. None of the above
Q. Which of the following operations has the worst time complexity in a singly linked list?
  • A. Accessing an element
  • B. Inserting an element
  • C. Deleting an element
  • D. Traversing the list
Q. Which of the following operations is guaranteed to be O(log n) in an AVL tree?
  • A. Insertion
  • B. Deletion
  • C. Searching
  • D. All of the above
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