# Interview Questions

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#### Q6: How do Insertion sort, Heapsort, Quicksort, and Merge sort work?

Insertion sort  sequentially accepts array items and keeps a sorted subfield on the left-hand side of the point at present. It achieves it by taking an element in the sorted array, determining its right position, and shifting all of the subsequent elements to 1.

Heapsort  begins the construction of a max heap. An almost full binary heap, in which every parental node is greater or equal to its offspring, is a binary max heap. The heap is saved in the same memory as the original display items. After the heap has been constructed, the array is replaced. We then take the first element and delete the heap property, decreasing the heap size by 1 and placing the maximum element at the end of it. This is continued until we empty the heap, which initially results in the lowest element and the subsequent elements are successively bigger.

Quicksort  The first (left) member of the array is taken as a pivot point. Then we compare it with every aspect below. We shift one smaller one to the left if we discover one smaller. This movement is accomplished rapidly by swapped the element after the pivot point and swapped the pivot point with the element thereafter. We take all of the points on the left side of the pivot, and we call quicksort on that subface, and do the same for all of the points on the right side of the pivot. The recursion is carried on until the 0-1 elements in length are subarrays.

Merge sort  Halves the array supplied recursively. On the trivial length of subarrays, fusion starts. The fusion of the smallest element between two adjacent subarrays continues the procedure until all items are sorted. On pairs of neighboring sub-ranges, the procedure is repeated until we reach the start array and are sorted.

#### Q7: What is Dijkstra's shortest path algorithm?

Ans: The algorithm of Dijkstra is a method to determine the shortest path of a weighted network from an initial node to the destination node. The technique builds a tree of shortest routes to all other nodes in the graph from the starting vertex and source vertex.

Suppose you wish to get as quickly as possible from house to office. You know that certain highways are quite crowded and difficult to use, therefore these borders weigh heavily. The shortest-path tree determined on the algorithm in the Dijkstra algorithm attempts to prevent borders of a bigger size.

#### Q8: Explain what is Skip list?

Ans: Save the data structuring technique list where the algorithm may be used in a symbol table or dictionary to search, delete, and insert items. Each entry is shown in a skip list with a node. The key value content is returned by the search function. The insert operation assigns a new value to a given key, whereas the delete function removes the provided key.

#### Q9: What are Red-Black Trees and B-Trees? What is the best use case for each of them?

Ans: Red-Black Trees and B-Trees are both balanced search trees that may be used for objects which can be specified by a comparison operator. You may operate in O(log N), such as minimum, maximum, predecessor, successor, insert and delete (with N being the number of elements). They may therefore be used to create a map, priority queue, or database index, to mention a few examples.

Binary Search Trees is an enhancement for Red-Black Trees. Binary Search Trees do the specified activities with binary trees, however, tree depth is not regulated – therefore it can take much longer than intended. The Red-Black Trees tackle this problem by designating red or black on all nodes in the tree and by defining restrictions on the processing of specific locations between nodes. This approach ensures that the longest branch is not more than twice as long as the smallest branch without too much detail, such that each branch is shorter than 2*log_base2(N).

It's great for carrying out ordered maps and priority queues. B-trees are not divided in 2 (as is characteristic of binary arbors) into K-2K branches (for a specified K number). They act much like a binary search tree other than that. The advantage is that access procedures may be reduced, which is especially beneficial when data is kept in a secondary or remote location. This enables us to request information in bigger quantities and our new request is ready to be processed when we complete the processing of an existing request. This structure is commonly utilized in database implementation as several secondary storage devices have access.