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How can you merge two binary search trees into a single binary search tree?

To merge two binary search trees into a single binary search tree, you can perform an in-order traversal on each tree to extract their elements, combine the elements into a single sorted list, and then construct a new binary search tree from the sorted list. This process ensures that the resulting tree maintains the binary search tree property.


What is binary linked list?

There is no such thing. There are binary trees and linked lists.


Why you used link list in binary tree?

Linked list was introduced to reduce the space wastage done by array & also to make easier the insertion and deletion of elements from a list. A binary tree contains nodes of elements where insertion,deletion & searching is frequently done. So to make these operations easier linked list is used.


How do you compare elements of a linked list. e.g an element should not be input when the same value already exists..?

In a linked list, if you want to prevent elements with the same key from being inserted twice, then you need to search the list prior to insert for that key. Iterate through the list, comparing elements with the element being inserted. If you encounter end-of-list, then insert the new element, otherwise throw whatever exception or indicate whatever error desired. Note that this is a full linear search. Statistically, if an element is to be found, it will be found at the halfway point, assuming uniformly random distribution of data. In the worst case, if the element is not found, it will always take a full search to prove that. This is not a very efficient use of a linked-list. It would be better to use some kind of ordered list, perhaps a dynamic array with binary search, or a balanced binary tree, which has similar search performance but one with the most cost to design and implement. You could keep the linked list in order, by inserting each element before the element that has higher key value. This would reduce search time to half, but that is still proportional to list size, not log 2 of list size like binary search is. Sorry, every answer has its tradeoffs.


What assumption about the list is made when binary search is conducted?

Binary search requires that the list be in search key order.


Complexity of an algorithm in data structure?

* search array => O(1) linked list=> O(n) binary tree=> O(log n) hash=>O(1) * search array => O(1) linked list=> O(n) binary tree=> O(log n) hash=>O(1)


How do you compare items in a linked list?

You compare items in a linked list by searching for them. Iterate through the list, comparing elements with the search key. If you encounter end-of-list, then the key is not found, otherwise you have found the element desired. Note that this is a half linear search. Statistically, if an element is to be found, it will be found at the halfway point, assuming uniformly random distribution of data. In the worst case, if the element is not found, it will always take a full search to prove that. You could keep the linked list in order, by inserting each element before the element that has higher key value. This would reduce search time to half, because searching would stop with the element with higher key value. Searching is not a very efficient use of a linked-list. It would be better to use some kind of ordered list, perhaps a dynamic array with binary search, or a balanced binary tree, which has similar search performance but one with the most cost to design and implement. Linked-lists are better for keeping elements in the order they were encountered or inserted, such as processing tokens in a compiler. Sorry, but every solution has its tradeoffs.


How do you overcome drawbacks of linked list?

Overcoming the "drawbacks" of a linked list requires knowing what drawback is at stack. If you need to iterate backwards as well as forwards, then you could create a doubly linked list. If you need to search for elements quickly, then you could implement a binary tree. If you have a static size, then you could implement an array. It's all a matter of tradeoff, and of what your particular issue is... Its badsector... According to my self disadvantage of link list that searching in link list is sequential if you compare it with arrays its very slow. Because in link list we have to search every node for that. if any one uses binary tree that is in some cases more faster than arrays.


Which type of search algorithm checks every element on the list in sequence until a matching data is found?

It's called "Linear Search". If the list is sorted, then it is possible to perform more advanced searches like binary search. If the list isn't sorted, then you can either sort the list first and then binary search or simply use a linear search. Linear search is typically a brute force solution when the data isn't "planned" or if the data is stored in a linked list where random access of the values in the list is slow.


What are the drawbacks of the binary search?

The only drawback I know of is that binary search requires that the list already be sorted. So if you have a really large unsorted list than binary search would not be the best option.


What are the advantages and disadvantages of binary search algorithms?

the major limitation of binary search is that there is a need of sorted array to perform binary search operation. if array is not sorted the output is either not correct or may be after a long number of steps and according to data structure the output should come in minimum number of steps.


Which is faster binary tree or binary search tree?

A tree doesn't do anything so it has no speed...