What is the time complexity of delete function in the hash table using a doubly linked list? a) O(1) b) O(n) c) O(log n) d) O(n log n)

Inserting a value in an unsorted linked list has the following big-O running time     a. O (1)   b. O (log n)   c. None of the above   d. O (n)   e. O (n2)

- In class HashTable implement a hash table and consider the following:(i) Keys are integers (therefore also negative!) and should be stored in the tableint[] data.(ii) As a hash function take h(x) = (x · 701) mod 2000. The size of the table istherefore 2000. Be careful when computing the index of a negative key. Forexample, the index of the key x = −10 ish(−10) = (−7010) mod 2000 = (2000(−4) + 990) mod 2000 = 990.Hence, indices should be non-negative integers between 0 and 1999!(iii) Implement insert, which takes an integer and inserts it into a table. Themethod returns true, if the insertion is successful. If an element is already inthe table, the function insert should return false.(iv) Implement search, which takes an integer and finds it in the table. The methodreturns true, if the search is successful and false otherwise.(v) Implement delete, which takes an integer and deletes it form the table. Themethod returns true, if the deletion is successful and false otherwise.(vi)…

The removeMin operation for both the linked and array implementation of a Minheap is: O O(1) O O(logn) O O(n?) O O(n) O O(nlogn)

How can a hash table improve efficiency over a linear list? Problem?

What is the worst-case performance of a lookup operation in a hashmap and why? Group of answer choices A- O(1), hashmap always has a constant time lookup, and that is why we like using this associative data structure.   B- O(lg(n)) hashmap has a log(n) lookup because we are able to perform a binary search on the keys because our hashmap always maintains a sorted order of entries added.   C- O(n) because we can have a bad hash function that puts all of our items in the same bucket, thus we would have to iterate through all n items.

The Big O value of hashing is: O a. O(log N) O b. O(N) Oc O(N*Log N) O d. 0(1)

What is the average-case runtime required for a successful operation in a hash table using chaining where there are m buckets and n items in the hash table? Select one: a. O( n/m ) b. O(n) The answer depends on both n and m c. O( 1) d. O(m)

Consider the following algorithm that uses a sorted list of n elements (alist). What is the worst case runtime of this algorithm? for each element in alist    1. ask the user for an input, call it value    2. search value in alist using binary search    3. if value exists in alist, print "successful"       otherwise print "unsuccessful"      Question options: a. O(log n) b. O(n) c. O(n log n) d. O(2^n) e. O(n^2) f. O(1)

We create a Hash-table of integers where the hash function returns the first digit of the integer(For example, for 33 it returns 3). If we use a binary search tree as the value storage of our hash-table, what is the time-complexity to look up an integer in it?*         O(Log(N))       O(N*Log(N))       O(N)       O(N^2)