mcqs on dat structure

Data Structures and Algorithms Important MCQs for LCC

If you want to prepare academic tests of ICTOs, Cyber Security, Cypher Jobs, in Pak Army, Pak Navy or in Pakistan Air Force then see the important questions of Data Structure and much more.

  • Queues are                         .  (Data structures that follow the First-In-First-Out (FIFO) principle)
  • In a queue, new elements are added at the                         .  (Rear)
  • In a queue, elements are removed from the                         .  ( Front)
  • The operation to add an element to a queue is called                         .  (Enqueue)
  • The operation to remove an element from a queue is called                         . (Dequeue)
  •                          data structure is commonly used to implement a queue.  (Linked list)
  • The maximum number of elements that a queue can hold is called its                         . (Capacity)
  • When a queue is full and no more elements can be added, it is said to be                         .  (Overflowing)
  • When a queue is empty and no elements are present, it is said to be                         . (Underflowing)
  • The time complexity of enqueue and dequeue operations in a queue implemented using an array is                         .  (O(1) for enqueue and O(n) for dequeue)
  • The time complexity of enqueue and dequeue operations in a queue implemented using a linked list is                         .  (O(1) for both enqueue and dequeue)
  • A circular queue is a variation of a queue where                         .  (Rear and front are connected, forming a circular structure)
  •                          is not a common application of queues.  (Dictionary implementation)

MCQs on Data Structure with Answers Free

See more questions of Computer particularly related to Data Structure which are given below.

  • A priority queue is a variation of a queue where                         .  ( Elements are stored based on their priority value)
  •                          is not a standard operation in a queue.  (Insert)
  • A graph is                         .  (A non-linear data structure)
  • In a graph, the elements are called                         (Vertices)
  • The connections between elements in a graph are called                        . (Edges)
  • A graph can be represented using                         .  (Arrays, Linked lists, Matrices)
  • The number of edges connected to a vertex in a graph is called its                         . (Degree)
  • A graph is said to be directed if                         .  (The edges have a specific direction)
  • A graph is said to be undirected if                         .  (It is acyclic and connected)
  • In a weighted graph, each edge                         .  (Has a label or weight associated with it)
  • The degree of a vertex in a directed graph is equal to                         . (The sum of incoming and outgoing edges)
  • The degree of a vertex in an undirected graph is equal to                         .  (The sum of incoming and outgoing edges)
  • A connected graph is a graph in which                         .  (There is a path between every pair of vertices)
  • A cycle in a graph is                         .  (A closed path that starts and ends at the same vertex)
  •                          is not a common representation of a graph.  (Breadth-first search (BFS))

Data Structure Multiple Choice Questions with Answers

Most important questions are given related to Data Structure which were part of the ICTOs academic tests. If you want to prepare initial tests of ICTOs of IT branch of PAF or Navy then given questions are very helpful to pass the academic test.

  • The time complexity of searching for a vertex in an adjacency list representation of a graph is                         .   (O(1))
  •                          is not a standard traversal algorithm for graphs.  (Dijkstra’s algorithm)
  • Hashing is                         .   (A data storage technique)
  • In hashing, data elements are stored in a                         .  (Hash table)
  • The key used in hashing is typically                         .  (A number)
  • The process of converting a key into a smaller fixed-size value is called                         .  (Compression)
  • The smaller fixed-size value obtained from a key is called                         .   (Hash)
  • The function used to compute the hash value from a key is called                         . (Hash function)
  • One of the main goals of a good hash function is to                         . (Minimize collisions)
  • A collision in hashing occurs when                         .  (Two different keys produce the same hash value)
  • The technique used to handle collisions in hashing is called                         . (Collision resolution)
  • Chaining is a collision resolution technique where                         .  (Colliding keys are stored in a linked list at the same hash index)
  • Probing is a collision resolution technique where                         .  (Colliding keys are rehashed using a different hash function)
  • Linear probing is a type of probing that                         .  (Probes the next available slot in the hash table for colliding keys)
  • Load factor in hashing refers to                         . ( The ratio of occupied slots to the total number of slots in the hash table)
  • The time complexity of searching for a key in a hash table is typically                         . (O(1))
mcqs on data structure

Data Structure and Algorithm MCQs for ICTO Initial Tests

Most important questions of Data Structure which are very important for the initial tests of Pak Army Jobs of ICTOs and PAF IT Branch tests.

  •                          is not a common hashing application.  (Binary search tree traversal)
  • A linked list is                         .  (A linear data structure)
  • In a linked list, elements are stored in                         .  (Dispersed memory locations)
  • Each element in a linked list is called a                         .  (Node)
  • In a singly linked list, each node contains                         .  (Data and a pointer to the next node)
  • In a doubly linked list, each node contains                         .  (Data and pointers to both the previous and next nodes)
  • The first node in a linked list is called the                         .  (Head node)
  • The last node in a linked list is called the                         .  (Tail node)
  • The time complexity of searching for an element in a linked list is typically                          ( O(N))
  • The time complexity of inserting an element at the beginning of a linked list is                         .  ( O(1))
  • The time complexity of deleting an element from the beginning of a linked list is                         .  (O(1))
  • The operation that allows us to examine the topmost element of a stack without removing it is called                         . (Peek)
  • Stacks can be implemented using                         .  (Arrays, Linked lists, Trees)
  •                          is not a common application of stacks.  (Searching and sorting algorithms)
  • BFS is                         (A searching algorithm)
  • The time complexity of inserting an element at the end of a linked list is                          (O(1))
  • The time complexity of deleting an element from the end of a linked list is                         .  (O(N))
  • The process of traversing a linked list from the beginning to the end is called                         .  (Traversal)
  •                          is not a disadvantage of linked lists.  (Linked lists have fixed size)
  • Circular linked lists are                         .  ( Linked lists with a circular reference)
  • An array is                         .  (A linear data structure)
  • In an array, elements are stored in                         .  (Contiguous memory locations)
  • The index of the first element in an array is typically                         .  (0)
  • The index of the last element in an array of size N is                         .  (N-1)
  • The time complexity of accessing an element in an array is typically                         . (O(1))
  • The time complexity of searching for an element in an unsorted array is typically                         . (O(N))
  • The time complexity of searching for an element in a sorted array using binary search is typically                         .  (O(log N))
  • The time complexity of inserting an element at the end of an array is                         . (O(1))
  • The time complexity of inserting an element at the beginning of an array is                         .  (O(N))
  • The time complexity of deleting an element from the end of an array is                         .  (O(1))
  • The time complexity of deleting an element from the beginning of an array is                         .  (O(N))
  • The maximum number of elements that can be stored in an array is determined by                         . (The size of the array)
  • Dynamic arrays are                         ( Arrays that can change their size during runtime)
  • Multidimensional arrays are                         .  (Arrays with more than one dimension)
  •                          is not a common sorting algorithm.  (Graph Sort)

Online Free Questions of Data Structure for Army and PAF Initial Tests

Most important past experiences of the questions which come in the initial tests of ICTO and IT branch of Army, Navy and PAF branch tests.

  •                          sorting algorithm has the worst-case time complexity of O(n2). (Insertion Sort)
  •                          sorting algorithm has the best-case time complexity of O(n).  (Counting Sort)
  •                          is not a disadvantage of arrays.  (Random access is not possible)
  • A stack is                         .  (A linear data structure)
  • In a stack, the insertion of an element is called                         (Push)
  • In a stack, the removal of an element is called                         (Pop)
  • The order in which elements are inserted and removed from a stack is                         .  (Last In First Out (LIFO))
  • The topmost element in a stack is the one that                         .  (Was inserted last)
  • The time complexity of inserting an element into a stack is typically                         . (O(1))
  • The time complexity of removing an element from a stack is typically                         . (O(1))
  • BFS explores a graph in                         order.  (Breadth-first)
  • BFS uses a data structure called a                         .  (Queue)
  • In BFS, the nodes are visited in the order of their                         .  (Distance from the source)
  • BFS is best suited for finding the                         .  (Shortest path in a graph)
  • The time complexity of BFS on a graph with V vertices and E edges is                         . (O(V + E))
  • BFS guarantees finding the shortest path in an unweighted graph if                         .(The graph is connected)
  • BFS can be used to detect                         . (Cycles in a graph, Bipartite graphs, Strongly connected components in a directed graph)
  • BFS can be implemented using                         . (Arrays, Linked lists, Queues)
  •                          data structure is commonly used to store the visited nodes during BFS.  (Queue)
  •                         sorting algorithm is based on the divide-and-conquer strategy. (Quick Sort)
  •                          sorting algorithm is stable, meaning it preserves the relative order of elements with equal values. (Merge Sort)
  •                          sorting algorithm works by repeatedly swapping adjacent elements if they are in the wrong order. (Bubble Sort)
  •                          sorting algorithm uses a binary tree-like data structure called a heap. (Heap Sort)
  •                          sorting algorithm is suitable for sorting elements in external memory or large datasets that do not fit in main memory.   (External Sort)
  •                          sorting algorithm has an average time complexity of O(n log n) and uses the “divide and conquer” approach.  (Quick Sort)

See More

  • Repeated Questions of Fundamental Programming for Army Tests (Download)
  • OOPs MCQs for ICTO Academic Tests (Download)
  • Online Past Tests of ICTOs Academic Tests for Army Jobs (Download)
  • Past Tests of Verbal Intelligence Tests of ICTOs (Download)
  • Non-Verbal Intelligence Tests of ICTOs Tests Intelligence (Download)

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