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## Self Balancing Binary Search Tree Multiple choice Questions and Answers (MCQs)

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Question 6 [CLICK ON ANY CHOICE TO KNOW MCQ multiple objective type questions RIGHT ANSWER] |

**Which of the following is a self - balancing binary search tree?**

2-3 tree | |

Threaded binary tree | |

AA tree | |

Treap |

Question 6 Explanation:

An AA tree, which is a variation of red-black tree, is a self - balancing binary search tree. 2-3 is B-tree of order 3 and Treat is a randomized binary search tree. A threaded binary tree is not a balanced tree.

Question 7 [CLICK ON ANY CHOICE TO KNOW MCQ multiple objective type questions RIGHT ANSWER] |

**A self - balancing binary search tree can be used to implement .....**

Priority queue | |

Hash table | |

Heap sort | |

Priority queue and Heap sort |

Question 7 Explanation:

Self-balancing binary search trees can be used to construct and maintain ordered lists, to achieve the optimal worst case performance. So, self - balancing binary search tree can be used to implement a priority queue, which is ordered list.

Question 8 [CLICK ON ANY CHOICE TO KNOW MCQ multiple objective type questions RIGHT ANSWER] |

**In which of the following self - balancing binary search tree the recently accessed element can be accessed quickly?**

AVL tree | |

AA tree | |

Splay tree | |

Red - Black tree |

Question 8 Explanation:

In a Splay tree, the recently accessed element can be accessed quickly. In Splay tree, the frequently accessed nodes are moved towards the root so they are quick to access again.

Question 9 [CLICK ON ANY CHOICE TO KNOW MCQ multiple objective type questions RIGHT ANSWER] |

**The minimum height of self balancing binary search tree with n nodes is .....**

log_{2}(n) | |

n | |

2n + 1 | |

2n - 1 |

Question 9 Explanation:

Self - balancing binary trees adjust the height by performing transformations on the tree at key insertion times, in order to keep the height proportional to log

_{2}(n).Question 10 [CLICK ON ANY CHOICE TO KNOW MCQ multiple objective type questions RIGHT ANSWER] |

**Binary tree sort implemented using a self balancing binary search tree takes O(n log n) time in the worst case but still it is slower than merge sort.**

True | |

False |

Question 10 Explanation:

The worst case performance of binary tree sort is O(n log n) when it is implemented using a self balancing binary search tree. Self balancing binary search trees perform transformations to balance the tree, which caused balancing overhead. Due to this overhead, binary tree sort is slower than merger sort.

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