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JNTU ONLINE EXAMINATIONS [Mid 2 - ads]

1. Which of the following is not a correct statement [01D01]1. internal sorting is used if the number of items to be sorted is very large 2. External sorting is used if the number of items to be sorted is very large 3. External sorting needs auxiliary storage 4. Internal sorting needs auxiliary storage

2. There are 4 different algorithms A1,A2,A3,A4 to solve a given problem with the order log(n),log(log(n)),nlog(n),n/log(n) respectively. Which is the best algorithm? [01D02]

1. A1 2. A2 3. A3 4. A4

3. For merging two sorted lists of sizes m and n into a sorted list of size m+n, requires _ _ _ _ _ _ _ _ no.of comparisons [01M01]

1. O(m) 2. O(n) 3. O(m+n) 4. O(log(m)+log(n))

4. Given two sorted list of size 'm' and 'n' respectively. The number of comparisons needed by the merge sort algorithm will be [01M02]

1. m x n 2. maximum of m,n 3. minimum of m,n 4. m+n-1

5. Merge sort uses [01M03]1. divide and conquer strategy 2. backtracking approach 3. heuristic approach 4. greedy approach

6. Which of the following sorting algorithm has the worst time complexity of nlog(n)? [01S01]

1. Heap sort 2. Quick sort 3. Insertion sort 4. Selection sort

7. Sorting is not useful for [01S02]1. report generation 2. minimizing the storage needed 3. making searching easier and efficient 4. responding to queries easily

8. In a binary search tree keys are inserted in the order {1,2,3.........n} as resulr? Find

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insert, delete operations take _ _ _ _ _ _ _ _ _ _ time. [02D01]1. O (long n) 2. O (n) 3. O (n long n) 4. O (n2)

9. A binary search tree is constructed with the following keys 20,22,26,21,13,19,18,15,26,28 The above keys are inserted in that order. Then the total keys in the left sub tree and the right sub tree of the tree or respectably. [02M01]

1. 5,5 2. 6,4 3. 7,3 4. 4,6

10. In indexed binary search tree leftsite field contains [02S01]1. no of elements in left sub tree 2. no of elements in left sub tree +1 3. Value of left leaf node 4. no of left leaf node +1

11. In indexed binary search tree left size field also gives the _ _ _ _ _ _ _ _ _ of an element with respect to the elements in its sub tree [02S02]

1. Sorted order 2. Median 3. Index 4. Rank

12. The balance factor of a node x in a binary tree is 3. There are 2 nodes in the right sub tree of x. There must be _ _ _ _ _ _ _ _ nodes in the left sub tree of x [03D01]

1. 2 2. 0 3. 5 4. 3

13. The permissible balance factors of an AVL tree are [03M01]1. 1,0,-2 2. -1,0,1 3. 0,1,2 4. -1,0,2

14. The height of an AVL Tree with n elements is [03S01]1. n 2. n2 3. n logn 4. log n

15. AVL tree is a _ _ _ _ _ _ _ _ _ binary tree [03S02]1. Complete 2. Full


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3. Height balanced 4. Skewed

16. After inserting an element in AVL tree, node A become imbalanced. Then new element added is the right child of right grand child of node A. Then the imbalances is of type [04D01]

1. RL 2. RR 3. LR 4. LL

17. If we insert an element in the right side of the left sub tree of node A in an AVL tree then the imbalance is of type [04M01]

1. RL 2. RR 3. LR 4. LL

18. The transformation done to remedy _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ imbalances is causual due in insectrum in as AVL tree often called single rotation [04S01]

1. LL & RR 2. LL & LR 3. LR & RL 4. RR & RL

19. The transformation done to remedy _ _ _ _ _ _ _ _ _ _ _ imbalances casul due to insertion in a AVL tree is often called double rotation. [04S02]

1. LL & RR 2. LL & LR 3. LR & RL 4. RR & RL

20. In AVL tree the transformation for an _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ imbalance can be viewed as an RR rotation followed by an LL rotation. [04S03]

1. RL 2. LR 3. RR 4. LL

21. In R0 Rotation the node which is imbalanced will be moving towards [05D01]1. Left sub tree 2. Right Subtree 3. root 4. not moving

22. In deletion of AVL search tree which of the following is not classified imbalance [05M01]1. R0 2. R2 3. R1 4. R-1


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23. In LR Rotation the node which is imbalanced is replaced with [05S01]1. root of left sub tree 2. Root of right subtree 3. left child of right subtree 4. right child of left subtree

24. In RL Rotation the node which is imbalanced is replaced with [05S02]1. root of left sub tree 2. Root of right subtree 3. left child of right subtree 4. right child of left subtree

25. In RR rotation the node which is imbalanced is replaced with [05S03]1. root of left sub tree 2. Root of right subtree 3. left child of right subtree 4. right child of left subtree

26. If a new node is added on the left side of left sub tree and tree is imbalance then the balance factor of the node which is imbalanced is [05S04]

1. 0 2. 2 3. -2 4. either 2 or -2

27. The time complexity of indexed search method is _ _ _ _ _ _ _ _ _ _ [06D01]1. O(h) 2. O(n) 3. O(n log n) 4. O(log n)

28. _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ is derived from an ordinary binary search tree by adding the field left size to each tree node. [06D02]

1. Binary search tree with duplicates 2. indexed binary search tree 3. Lexographical binary search tree 4. binary tree

29. In a binary search tree if the key element is greater than root element then _ _ _ _ _ _ _ _ _ sub tree must be searched [06M01]

1. right 2. left 3. center 4. root

30. In a binary search tree if the key element is less than root element then _ _ _ _ _ _ _ _ _ sub tree must be searched [06M02]

1. right 2. left 3. center


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4. root 31. The time complexity of search method in binary search tree eith n-nodes of hight h is _

_ _ _ _ _ _ [06M03]1. O(h) 2. O(n) 3. O(n log n) 4. O(log h)

32. Which traversal of a binary search tree traverses visits to the nodes in ascending order of key values? [06S01]

1. In Order 2. Pre Order 3. Post Order 4. Past Order

33. In Binary search tree, if the element to be inserted is less than the root node, then the element is inserted in [06S02]

1. Left sub-tree 2. Root 3. Right sub-tree 4. Cannot be inserted

34. In binary search tree, if the element to be inserted is greater than the root node, the element is inserted in [06S03]

1. Left sub-tree 2. Root 3. Right sub-tree 4. Cannot be inserted

35. Which of the following statements is false with respect to binary search tree ? [06S04]1. Root has maximum element 2. Left child is less than parent node 3. Right child is greater than left child 4. Right child is greater than parent node

36. If root is null it means that search tree has _ _ _ _ _ _ _ _ _ _ _ _ _ [06S05]1. no element 2. unknown elements 3. uncountable elements 4. 1 element

37. To delete a node that has exactly two non empty sub trees [07D01]1. The pointer in the parent node is made null 2. Node is replaced by smallest element in right sub tree 3. Node is replaced by its child 4. Node's parent will point to node's child

38. To delete a leaf node in binary search tree [07M01]1. The pointer in the parent node is made null 2. Node is replaced by smallest element in right sub tree


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3. Node is replaced by its child 4. Node's parent will point to node's child

39. To delete a root node that has exactly one non-empty sub tree [07M02]1. The pointer in the parent node is made null 2. Node is replaced by smallest element in right sub tree 3. Node is replaced by its child 4. Node's parent will point to node's child

40. Before inserting an element in a binary search tree we must perform _ _ _ _ _ _ _ _ _ _ _ operation to check distinct property. [07S01]

1. assend 2. delete 3. search 4. create

41. In Binary search tree if the search is _ _ _ _ _ _ _ _ _ then the element is inserted at the point the search terminated [07S02]

1. Successful 2. True 3. Unsuccessful 4. Correct

42. Time complexity of insert procedure in binary search tree with hight h, and n nodes is [07S03]

1. O(h) 2. O(n) 3. O(n log n) 4. O(log)

43. An n element AVL tree with height h can be searched in [08D01]1. o(log h) 2. O(h) 3. O(h log h) 4. O(n)

44. AVL Trees are normally represented using [08D02]1. Array's 2. Adjacency list 3. Linked nodes 4. Adjacency matrix

45. An n- element AVL tree can be searched in [08M01]1. o(n) 2. o(n2) 3. o(n logn) 4. o(log n)

46. All AVL Trees are basically [08M02]1. quad trees 2. empty trees


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3. binary search trees 4. B-Trees

47. Trees with a worst case height of o(log n) are called [08S01]1. Search tree 2. Binary search tree 3. Balanced search tree 4. Threaded binary tree

48. AVL tree was not developed by _ _ _ _ _ _ _ _ _ [08S02]1. Velskii 2. Anderson 3. Landis 4. Adelson

49. Which of the following balance factors is not allowed in AVL trees [08S03]1. -1 2. 0 3. 1 4. 2

50. The difference between the heights of left subtree & right subtree is called [08S04]1. Balance factor 2. height difference 3. Load balance 4. Rank

51. After inserting an element in AVL tree node A became imbalanced. The new element added is the left child of right grand child of node A. Then the imbalance is of type [09D01]

1. RL 2. RR 3. LR 4. LL

52. After inserting an element in AVL tree node A become imbalanced. The new element added is the left child of left grand child of node A then the imbalance is of type [09D02]

1. RL 2. RR 3. LR 4. LL

53. In AVL trees the transformation for an _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ imbalance can be viewed as an LL rotation followed by an RR rotation. [09M01]

1. RL 2. LR 3. RR 4. LL

54. Let `E' be the element to be inserted in AVL tree, if already an element with the same key value `E' is found in AVL tree then [09S01]


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1. new element replaces already existing element 2. insertion fails 3. new element becomes root node 4. new element will be right child of existing element

55. An AVL Tree after insertion becomes imbalance, if balance factor of a node is [09S02]1. 0 2. 1 3. -1 4. 2

56. After deletion of a mode in an AVC tree a maximum of _ _ _ _ _ _ _ _ _ _ is sufficient to restore balance [09S03]

1. 0 rotations 2. 1 rotations 3. 2 rotations 4. 3 rotations

57. In R0 imbalance of AVL tree the significance of R is [10D01]1. Deleted element is in right subtree 2. Deleted element is in left subtree 3. Deleted element is root element 4. No element is deleted

58. In L1 imbalance of AVL tree the significance of L is [10D02]1. Deleted element is in right subtree 2. Deleted element is in left subtree 3. Deleted element is root element 4. No element is deleted

59. In deletion of AVL search tree which of the following is not classified imbalance [10M01]1. L0 2. L1 3. L-1 4. L2

60. In AVL tree LL Rotation the node which is imbalanced will move towards its _ _ _ _ _ _ _ _ _ _ _ [10S01]

1. Left sub tree 2. Right sub tree 3. Root 4. not move

61. In a AVL tree RR rotation the node which is imbalanced will move towards _ _ _ _ _ _ _ _ _ _ _ _ [10S02]

1. Left sub tree 2. Right sub tree 3. Root 4. not move

62. If a new node is added on the right side and the AVL tree is imbalance then the balance


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factor of the node which is imbalanced is [10S03]1. 0 2. 2 3. -2 4. either 2 or -2

63. In LL Rotation the node which is imbalanced is replaced with its [10S04]1. root of left sub tree 2. Root of right subtree 3. left child of right subtree 4. right child of left subtree

64. In splay trees if the amortized costs are higher then the actual costs then potential is _ _ _ _ _ _ _ _ _ _ _ _ _ _ [11D01]

1. Decreasing 2. increasing 3. same 4. constant

65. In splay trees, if the amortized costs are lower then the actual costs then potential is _ _ _ _ _ _ _ _ _ _ _ _ _ [11D02]

1. Decreasing 2. increasing 3. same 4. constant

66. The run time for a splay (x) operation is proportional to the length of the _ _ _ _ _ _ _ _ _ _ _ _ path for x. [11M01]

1. Search 2. Join 3. Insert 4. Shortest

67. In splay trees the difference between concrete and amortized cost is charged against the _ _ _ _ _ _ _ _ _ _ _ _ of the data structure [11M02]

1. analysis 2. search 3. potential 4. running time

68. Splay trees are invented by [11S01]1. Sleator & Tarjan 2. Sleater &Hoare 3. Hoare &knuth 4. knuth &Tarjan

69. The Splay operation moves element to _ _ _ _ _ _ _ _ _ _ _ _ of the tree [11S02]1. Leaf 2. Right sub tree 3. Root


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4. Left sub tree 70. The time complixity of maintaining a splay trees is analyzed using [11S03]

1. ABC analysis 2. Amortised analysis 3. cost analysis 4. search analysis

71. Which of the following is not a splay tree operation. [11S04]1. search 2. split 3. Insert 4. Delete

72. _ _ _ _ _ _ _ _ _ _ _ _ _ _is essentially a binary tree with special update and access rules. [11S05]

1. B-Trees 2. M-way search tree 3. AVL trees 4. Splay trees

73. A Sequence of m operations on splay tree with initially n nodes takes time of the order of _ _ _ _ _ _ _ _ _ _ _ _ _ [11S06]

1. O (n�∗m) 2. O (n log n +m log n) 3. (n log n2) 4. O (n log n�∗m)

74. (x) To search AVL, Red-black, binary search trees same code can be used. (y) For isertion in to binary search tree and AVL tree same code can be used [12D01]

1. both (x) & (y) are correct 2. (x) is correct (y) is false 3. (x) is false (y) is correct 4. Both (x) & (y) are false

75. In a red black-tree (x) Every external node is colored black (y) The children of red node of black [12D02]

1. Both (x) and (y) are correct 2. (x) is correct (y) is false 3. (x) is false (y) is correct 4. Both (x) and (y) is false

76. In the Red Black Trees the external nodes are represented by _ _ _ _ _ _ _ _ _ _ [12S01]

1. Solid Square 2. Squares 3. Circles 4. Solid Circles

77. In Red-Black trees pointers from internal node to an external node are _ _ _ _ _ _ _ _ _ _ _ _ [12S02]


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1. Solid 2. Red 3. Black 4. Null

78. In Red-Black tress, red pointers are represented by _ _ _ _ _ _ _ _ _ _ _ _ _ [12S03]1. solid lines 2. red lines 3. thin lines 4. circles

79. In Red-Black trees every path from the root to an external node has _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ pointers [12S04]

1. Two black 2. one black 3. two red 4. one red

80. In Red-Black trees root node is _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ [12S05]1. Black 2. red 3. Null 4. No child

81. An n node red-black tree has the property that its height is _ _ _ _ _ _ _ _ _ [12S06]1. O(n log(n)) 2. O(n) 3. O(n2) 4. O(log(n))

82. If a non-leaf node is red then it has _ _ _ _ _ _ _ _ _ _ _ _ _ _ [12S07]1. only black Childs 2. only red Childs 3. both black & red child 4. no-child

83. _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ is a binary search tree with extra attribute i..e. color [12S08]

1. Black-white tress 2. Red-black trees 3. AVL trees 4. Balanced binary trees

84. A rotation is local operation in a search tree that preserves _ _ _ _ _ _ _ _ _ _ _ _ traversal key ordering [12S09]

1. Preorder 2. Post order 3. In order 4. Past order

85. Null nodes which terminates the tree are _ _ _ _ _ _ _ _ _ [12S10]


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1. Black 2. red 3. white 4. No child

86. A red-node cannot have _ _ _ _ _ _ _ _ [13D01]1. red child 2. black child 3. child 4. white child

87. There are never two _ _ _ _ _ _ _ _ _ _ _ _ links in a row [13D02]1. Black 2. White 3. Red 4. Orange

88. In Red black tress the value of any node is _ _ _ _ _ _ _ _ _ _ _ _ than the value of its left child [13M01]

1. equal 2. less 3. greater 4. No relation

89. In Red-black trees the value of any node is _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ than the value of its right child [13M02]

1. equal 2. less 3. greater 4. No relation

90. In _ _ _ _ _ _ _ _ _ _ _ trees each node may contain more than one key [13S01]1. Binary tree 2. AVL tree 3. B-Tree 4. Splay trees

91. _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ is an example of multiway tree _ _ _ _ _ _ _ _ _ _ [13S02]

1. Binary tree 2. AVL tree 3. B-Tree 4. Splay trees

92. _ _ _ _ _ _ _ _ _ _ _ _ Tress is designed especially for use on disk [13S03]1. Binary tree 2. AVL tree 3. B-Tree 4. Splay trees

93. A multiway tree of order m is an ordered tree where each node has _ _ _ _ _ _ _ _ _ _


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_ children [13S04]1. m 2. atmost m 3. at least m 4. not m

94. A B-tree of order m is an _ _ _ _ _ _ _ _ _ _ _ _ _ _ search tree [13S05]1. m+1-way 2. 2-way 3. m-1-way 4. m-way

95. In Red Black tress every path from the root to a leaf contains the same no.of [13S06]1. nodes 2. red nodes 3. leaf nodes 4. black nodes

96. In B-tree of order m the root has _ _ _ _ _ _ _ _ _ _ child nodes [14S01]1. atleast 2 2. m 3. m/2 4. zero

97. In B-tree of order m all external nodes are _ _ _ _ _ _ _ [14S02]1. at different levels 2. have 1 child node 3. at same levels 4. have two child nodes

98. In B-tree of order all is internal nodes, other than the root have _ _ _ _ _ _ _ _ children [14S03]

1. 2 2. m 3. o 4. m/2

99. Searching in an m-way search tree, we will get unsuccessful result in the following condition, if the search path heads to _ _ _ _ _ _ _ _ _ _ _ [14S04]

1. root node 2. leaf node 3. external node 4. internal node

100. In B-tree of height h containing n nodes the time complexity for search operation is _ _ _ _ _ _ _ _ _ _ _ _ _ _ [14S05]

1. o(h) 2. o(h�∗n) 3. o(log h) 4. o (hlog n)


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101. In B-tree of height h contains n-nodes the time complexity for insert operation is _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ [14S06]


102. In a B-tree of height h containing n nodes the time complexity of delete operation is _ _ _ _ _ _ _ _ _ _ _ _ _ [14S07]


103. In Deletion from a B-tree case 2 is transformed into case 1 by replacing the deleted element with the _ _ _ _ _ _ _ _ _ _ _ _ element in its right neighboring sub tree [15D01]

1. Smallest 2. largest 3. leftmost 4. root

104. After deleting an element from a B-tree we merge two siblings into a single node under the condition. If the deleted node has _ _ _ _ _ _ _ _ _ [15D02]

1. extra element 2. leaf node 3. no extra element 4. is root

105. Deletion of element from a B-tree from a leaf that containing more than the minimum no. of elements requires _ _ _ _ _ _ _ _ _ _ [15M01]

1. modifying left sibling 2. modifying right sibling 3. modifying parent 4. Simple deletion of element

106. In Deletion from a B-tree case 2 is transformed into case 1 by replacing the deleted element with the _ _ _ _ _ _ _ _ _ _ _ element in its left neighboring sub tree [15M02]

1. Smallest 2. largest 3. leftmost 4. root

107. A B-tree of order m is also known as _ _ _ _ _ _ _ [15S01]1. Binary search tree 2. m-way search tree 3. m-ordered tree 4. ordered search tree

108. A 200-way search tree of height 8 can hold a minimum no. of _ _ _ _ _ _ _ _ _ _ nodes


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[15S02]1. 200 2. 8 3. 8�∗log 200 4. 2008-1

109. B-tree of order 3 is also known as _ _ _ _ _ _ _ _ _ _ [15S03]1. 2-3 tree 2. 3-4 tree 3. binary tree 4. Splay tree

110. B-Tree of order 2 are _ _ _ _ _ _ _ _ _ [15S04]1. Binary tree 2. Sticky binary tree 3. full binary tree 4. complete binary tree

111. Deletion of element in a B-tree is divided into _ _ _ _ _ _ _ _ _ _ _ _ _ _ cases [15S05]1. 1 2. 3 3. 2 4. 4

112. In the boyer moore algorithm if the pattern P is `àlgorithm" the comparison goes to the next character if the first character is [16D01]

1. a 2. 1 3. space 4. m

113. KMP algorithm is the improved version of _ _ _ _ _ _ _ _ _ _ _ _ algorithm [16D02]1. knuth 2. morris pratt 3. knuth morris 4. knuth pratt

114. In the boyer moore algorithm if the pattern P is `àlgorithm" Then the shift value of character a is [16M01]

1. 9 2. 1 3. 0 4. 8

115. In the boyer moore algorithm if the pattern P is `àlgorithm" Then the shift value of character g is [16M02]

1. 9 2. 6 3. 2 4. 3


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116. given string T and pattern P the pattern matching problem consists of finding a substring of _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ equal to _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ [16S01]

1. P ; ; ; ; ; ; ; ; ; ; P 2. T ; ; ; ; ; ; ; ; ; ; P 3. P ; ; ; ; ; ; ; ; ; ; T 4. T ; ; ; ; ; ; ; ; ; ; T

117. Which of the following is not an application of pattern matching algorithm [16S02]1. text editor 2. search engines 3. insertion 4. biological research

118. The brute force pattern matching algorithm compares the pattern P with the text T for _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ values [16S03]

1. consecutive 2. random 3. sorted 4. binary

119. _ _ _ _ _ _ _ _ _ _ _ algorithm is recommended for binary strings pattern matching [16S04]

1. Boyer moore 2. brute force 3. morris 4. KMP

120. _ _ _ _ _ _ _ _ _ algorithm is preferred for pattern matching when the length is of short duration [16S05]


121. _ _ _ _ _ _ _ _ _ algorithm is preferred for pattern matching if the size of string is large compared to the length of the pattern [16S06]


122. In the boyer moore algorithm let the string T be ``this is a test of the boyer moore algorithm" and the pattern P is ``algorithm" after the first comparison _ _ _ _ _ _ _ _ _ _ _ _ shift takes place [17D01]

1. good suffix shift 2. bad character shift 3. matching shift 4. non matching shift


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123. In the boyer moore algorithm _ _ _ _ _ _ _ _ _ _ _ _ function will calculate how far the pattern must be shifted if the character is found in the pattern [17D02]

1. last 2. prefix 3. first 4. end

124. In bad character shift the length of the shift is equal to the [17M01]1. 3 positions 2. zero positions 3. half of the pattern 4. length of the pattern

125. In the boyer moore algorithm let the string T be ``this is a test of the boyer moore algorithm" and the pattern P is ``algorithm" the first comparison takes place between [17M02]

1. a t 2. h l 3. a m 4. m m

126. In boyer moore algorithm _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ number of precomputed functions are there [17S01]

1. 1 2. 0 3. 2 4. 3

127. The boyer moore algorithm scans the characters of the pattern from _ _ _ _ _ _ to _ _ _ _ _ _ _ _ _ _ _ _ [17S02]

1. right , left 2. left ,left 3. a right , right 4. left ,right

128. In the boyer moore algorithm good suffix shift is also known as [17S03]1. bad character shift 2. matching shift 3. occurrence shift 4. non matching shift

129. In the boyer moore algorithm bad character shift algorithm is also known as [17S04]1. good suffix shift 2. matching shift 3. occurrence shift 4. non matching shift

130. In the boyer moore algorithm if the character being compared is existing in the pattern then _ _ _ _ _ _ _ _ _ _ _ _ _ shift will be performed [17S05]

1. good suffix shift


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2. bad character shift 3. occurrence shift 4. non matching shift

131. In the boyer moore algorithm if the character being compared is not present in the pattern then _ _ _ _ _ _ _ _ _ _ _ _ _ shift will be performed [17S06]

1. good suffix shift 2. bad character shift 3. matching shift 4. non matching shift

132. In boyer moore algorithm , in which heuristic that pattern P is compared with a sub sequence of T moving backwards [18D01]

1. looking glass heuristic 2. character jump heuristic 3. basic heuristic 4. boyer heuristic

133. In boyer moore algorithm , in which heuristic mismatch occurs [18D02]1. looking glass heuristic 2. character jump heuristic 3. basic heuristic 4. boyer heuristic

134. In KMP pattern matching algorithm the time complexity of pre processing function is [18M01]

1. O(n) 2. O( log n) 3. O( n2) 4. O(n log n)

135. In KMP pattern matching algorithm the pre processing function computes the _ _ _ _ _ _ _ _ _ _ _ _ _ _ of pattern matches within itself [18M02]

1. comparisons 2. shifting 3. number 4. mismatches

136. Brute force algorithm is also known as _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ algorithm [18S01]1. moore 2. boyer 3. naive 4. morris

137. In which pattern matching algorithm, character by character comparisons takes place [18S02]

1. brute force 2. boyer moore 3. knuth - morris 4. pratt


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138. In brute force pattern matching algorithm in case if a character is not matched then the _ _ _ _ _ _ _ _ _ _ _ is shifted one position [18S03]

1. pointer 2. pattern 3. string 4. character

139. Time complexity of brute force string matching algorithm is [18S04]1. Θ(n) 2. Θ(logn) 3. Θ(nlogn) 4. Θ(n2)

140. which of the following pattern matching algorithm does not require s pre processing on text or pattern [18S05]

1. Brute force 2. R obin karp 3. boyer 4. knuth morris pratt

141. In KMP pattern matching algorithm pre processing is done by an auxillary function known as [18S06]

1. failure function 2. prefix function 3. postfix function 4. insert function

142. A compressed trie is obtained from _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ [19D01]1. trie 2. standard trie 3. suffix trie 4. encoding trie

143. In compressed tries the chain of _ _ _ _ _ _ _ _ _ _ _ nodes are compressed [19D02]1. leaf 2. external 3. internal 4. redundant

144. A trie is useful when the set of keys is _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ [19M01]1. dense 2. sparse 3. empty 4. independent of set of keys

145. A compressed trie has internal nodes of degree atleast equal to [19M02]1. 0 2. 1 3. 2 4. 3


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146. The structures occur frequently in the area of information organization and _ _ _ _ _ _ _ _ _ _ [19S01]

1. search 2. storing 3. retrieval 4. management

147. Trie structures name is derived from the word [19S02]1. search 2. storing 3. retrieval 4. management

148. The method of searching in tries is analogous to _ _ _ _ _ _ _ _ [19S03]1. sorting 2. digital sorting 3. hashing 4. binary search

149. A trie structure is a complete _ _ _ _ _ _ _ _ _ _ _ _ _ tree [19S04]1. binary 2. search 3. B-tree 4. m- ary

150. Each node in a trie structure will not contain [19S05]1. pointer 2. dash 3. desired word 4. node number

151. A digital search tree is implemented using [19S06]1. binary tree 2. trie 3. binary search tree 4. B-tree

152. An inverted file is a file structure in which every list contain only _ _ _ _ _ _ _ _ _ record [20D01]

1. 0 2. 1 3. 2 4. 3

153. An inverted file is also known as _ _ _ _ _ _ _ _ _ _ _ _ [20D02]1. indeed sequential file 2. sequential file 3. random file 4. binary file

154. A standard trie supports insert in _ _ _ _ _ _ _ _ _ _ time where m is size of string


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parameter and d is size of the alphabet [20M01]1. O(d)�∗ O(m) 2. O(dm) 3. O( dm) 4. O(d+m)

155. A standard trie supports delete in _ _ _ _ _ _ _ _ _ _ time where m is size of string parameter and d is size of the alphabet [20M02]

1. O(d)�∗ O(m) 2. O(dm) 3. O( dm) 4. O(d+m)

156. which of the following operation is not supported by tries [20M03]1. sorting 2. insert 3. delete 4. find

157. _ _ _ _ _ _ _ _ _ _ _ _ is a compact data structure for representing a set of strings such as all the words in a text [20S01]

1. trie 2. tree 3. search engine 4. B- tree

158. In standard trie each node except the _ _ _ _ _ _ _ _ _ _ _ _ _ _ is labeled with a character [20S02]

1. leaf 2. external 3. internal 4. root

159. The path from the _ _ _ _ _ _ _ _ nodes to the root yield the string S [20S03]1. parent 2. external 3. internal 4. root

160. A standard trie uses _ _ _ _ _ _ _ _ _ _ space [20S04]1. O(n) 2. O(n2) 3. O(n log n) 4. O(log n)

161. A standard trie supports search in _ _ _ _ _ _ _ _ _ _ time where m is size of string parameter and d is size of the alphabet [20S05]

1. O(d)�∗ O(m) 2. O(dm) 3. O( dm)


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4. O(d+m)


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