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. If a binary search algorithm returns -1, what does it indicate?
  • A. The element is found
  • B. The element is not in the array
  • C. The array is empty
  • D. The array is sorted
Q. If a binary search is performed on a sorted array of size n, what is the space complexity?
  • A. O(1)
  • B. O(n)
  • C. O(log n)
  • D. O(n log n)
Q. If a binary search is performed on an array of 32 elements, how many iterations will it take in the worst case?
  • A. 4
  • B. 5
  • C. 6
  • D. 7
Q. If a binary search is performed on an array of size 16, how many comparisons are needed in the worst case?
  • A. 4
  • B. 5
  • C. 6
  • D. 7
Q. If a binary search is performed on an array of size 16, how many comparisons will be made in the worst case?
  • A. 4
  • B. 8
  • C. 16
  • D. 5
Q. If a binary search is performed on an array of size 16, how many comparisons will it take in the worst case?
  • A. 4
  • B. 8
  • C. 16
  • D. 5
Q. If a binary tree has 'n' nodes, what is the maximum height of the tree?
  • A. n
  • B. log n
  • C. n/2
  • D. n-1
Q. If a binary tree has 15 nodes, what is the maximum height of the tree?
  • A. 15
  • B. 4
  • C. 3
  • D. 5
Q. If a binary tree has a height of 'h', what is the minimum number of nodes it can have?
  • A. h
  • B. h + 1
  • C. 2^h - 1
  • D. 2^h
Q. If a binary tree has a height of h, what is the maximum number of nodes it can have?
  • A. 2^h - 1
  • B. 2^h
  • C. h^2
  • D. h!
Q. If a binary tree has n nodes, what is the maximum number of leaf nodes it can have?
  • A. n
  • B. n/2
  • C. n/3
  • D. n/2 + 1
Q. If a binary tree is balanced, what is the maximum height of the tree in terms of the number of nodes 'n'?
  • A. O(n)
  • B. O(log n)
  • C. O(n log n)
  • D. O(1)
Q. If a graph has 5 vertices and 10 edges, what is the maximum number of edges it can have?
  • A. 5
  • B. 10
  • C. 20
  • D. 25
Q. If a graph has 5 vertices and 10 edges, what is the maximum number of iterations Dijkstra's algorithm will perform?
  • A. 5
  • B. 10
  • C. 15
  • D. 20
Q. If a graph has 5 vertices and 10 edges, what is the maximum time complexity of Dijkstra's algorithm using an adjacency matrix?
  • A. O(10)
  • B. O(5^2)
  • C. O(5 log 5)
  • D. O(10 + 5^2)
Q. If a graph has 5 vertices and 7 edges, what is the maximum number of edges in a simple undirected graph?
  • A. 10
  • B. 12
  • C. 15
  • D. 20
Q. If a graph has 5 vertices and 7 edges, what is the maximum number of edges in a complete graph with 5 vertices?
  • A. 10
  • B. 12
  • C. 15
  • D. 20
Q. If a graph has 5 vertices and 7 edges, what is the maximum number of edges it can have?
  • A. 10
  • B. 15
  • C. 20
  • D. 25
Q. If a graph has 5 vertices and 7 edges, what is the maximum number of iterations Dijkstra's algorithm will perform?
  • A. 5
  • B. 7
  • C. 10
  • D. 12
Q. If a graph has a cycle, which traversal method can detect it?
  • A. Only BFS
  • B. Only DFS
  • C. Both BFS and DFS
  • D. Neither BFS nor DFS
Q. If a graph has negative edge weights, which algorithm can be used instead of Dijkstra's algorithm?
  • A. Prim's Algorithm
  • B. Kruskal's Algorithm
  • C. Bellman-Ford Algorithm
  • D. Floyd-Warshall Algorithm
Q. If a graph has negative weight edges, which algorithm can be used instead of Dijkstra's?
  • A. Prim's algorithm
  • B. Kruskal's algorithm
  • C. Bellman-Ford algorithm
  • D. A* algorithm
Q. If a graph has negative weight edges, which algorithm should be used instead of Dijkstra's algorithm?
  • A. Prim's algorithm
  • B. Kruskal's algorithm
  • C. Bellman-Ford algorithm
  • D. Floyd-Warshall algorithm
Q. If a graph has negative weight edges, which algorithm should be used instead of Dijkstra's?
  • A. Prim's algorithm
  • B. Kruskal's algorithm
  • C. Bellman-Ford algorithm
  • D. A* algorithm
Q. If a graph has V vertices and E edges, what is the space complexity of Dijkstra's algorithm using an adjacency list?
  • A. O(V)
  • B. O(E)
  • C. O(V + E)
  • D. O(V^2)
Q. If a graph has V vertices and E edges, what is the space complexity of Dijkstra's algorithm?
  • A. O(V)
  • B. O(E)
  • C. O(V + E)
  • D. O(V^2)
Q. If a graph has V vertices and E edges, what is the worst-case time complexity of Dijkstra's algorithm using an adjacency matrix?
  • A. O(V^2)
  • B. O(E log V)
  • C. O(V + E)
  • D. O(V^3)
Q. If a graph is represented using an adjacency matrix, what is the time complexity of BFS?
  • A. O(V + E)
  • B. O(V^2)
  • C. O(E)
  • D. O(V log V)
Q. If a queue is implemented using two stacks, what is the time complexity of dequeue operation in the worst case?
  • A. O(1)
  • B. O(n)
  • C. O(log n)
  • D. O(n^2)
Q. If a sorted array has 16 elements, how many comparisons will binary search make in the worst case?
  • A. 4
  • B. 5
  • C. 16
  • D. 8
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