# Fundamentals of data structures

OOP adopts a higher level of abstraction, namely objects. A data structure, like any other abstracted entity, is encapsulated as an object with state data and behavior functionality. An object is an instance of its class type. Parameters in method calls can now be objects of any specified type, possessing not only pure data, but also specified functional behavior.

Through encapsulation, a client can directly access only externally visible members of the ADT, namely its Application Programming Interface API , and is oblivious to the internal details, hence to any particular implementation, of the ADT. The interaction between the client and the ADT implementation is through this API which acts as a contract between them.

The output shows the position of element in array. Given an unordered list, we compare adjacent elements in the list, each time, putting in the right order of magnitude, only two elements.

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The algorithm hinges on a swap procedure. Knowing how many times to swap is important when implementing a bubble sort algorithm.

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To sort a list of numbers such as [3, 2, 1], we need to swap the elements a maximum of twice. This is equal to the length of the list minus 1.

### Importance

The quick sort algorithm falls under the divide and conquer class of algorithms, where we break divide a problem into smaller chunks that are much simpler to solve conquer. In this case, an unsorted array is broken into sub-arrays that are partially sorted, until all elements in the list are in the right position, by which time our unsorted list will have become sorted. This sorting algorithm begins by finding the smallest element in an array and interchanging it with data at, for instance, array index [0]. Starting at index 0, we search for the smallest item in the list that exists between index 1 and the index of the last element.

When this element has been found, it is exchanged with the data found at index 0. We simply repeat this process until the list becomes sorted. ShellSort is mainly a variation of Insertion Sort. The idea of shellSort is to allow exchange of far items. In shellSort, we make the array N-sorted for a large value of N. We keep reducing the value of N until it becomes 1. An array is said to be N-sorted if all sub-lists of every N'th element is sorted.

The idea of swapping adjacent elements to sort a list of items can also be used to implement the insertion sort. In the insertion sort algorithm, we assume that a certain portion of the list has already been sorted, while the other portion remains unsorted. With this assumption, we move through the unsorted portion of the list, picking one element at a time. With this element, we go through the sorted portion of the list and insert it in the right order so that the sorted portion of the list remains sorted.

The Comb Sort is a variant of the Bubble Sort. Bubble sort always compares adjacent values. So all inversions are removed one by one. Comb Sort improves on Bubble Sort by using gap of size more than 1. The gap starts with a large value and shrinks by a factor of 1. Thus Comb Sort removes more than one inversion counts with one swap and performs better than Bubble Sort.

Merge Sort is a Divide and Conquer algorithm. Meaning, the algorithm splits an input into various pieces, sorts them and then merges them back together.

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It divides input slice in two halves, calls itself for the two halves and then merges the two sorted halves. The merge function is used for merging two halves. Radix Sort is a clever and intuitive little sorting algorithm. Radix Sort puts the elements in order by comparing the digits of the numbers. Radix sort is an integer sorting algorithm that sorts data with integer keys by grouping the keys by individual digits that share the same significant position and value place value.

Radix sort uses counting sort as a subroutine to sort an array of numbers. Pancake sorting is the colloquial term for the mathematical problem of sorting a disordered stack of pancakes in order of size when a spatula can be inserted at any point in the stack and used to flip all pancakes above it.

A pancake number is the maximum number of flips required for a given number of pancakes.

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## Data Structures Fundamentals

A binary tree is a tree data structure in which each node has at most two child nodes, usually distinguished as "left" and "right". Nodes with children are parent nodes, and child nodes may contain references to their parents. Here is the source code of the Go program to implement Binary Tree. The Rabin-Karp algorithm is a string searching algorithm that uses hashing to find patterns in strings.

In computer science, a linked list is a linear collection of data elements, in which linear order is not given by their physical placement in memory. Each pointing to the next node by means of a pointer.

It is a data structure consisting of a group of nodes which together represent a sequence. In computer science, the median of medians is an approximate median selection algorithm, frequently used to supply a good pivot for an exact selection algorithm, mainly the quick-select, that selects kth smallest element. A stack is an ordered list in which all insertions and deletions are made at one end, called the top.

## Data Structures & Algorithm Basic Concepts - Tutorialspoint

A queue is an ordered list in which all insertions take place at one end, the rear, while all deletions take place at the other end, the front. The longest common subsequence LCS problem is the problem of finding the longest subsequence common to all sequences in a set of sequences often just two sequences. Write a program in Go which returns an LCS of two strings case-sensitive. Levenshtein distance LD is a measure of the similarity between two strings, which we will refer to as the source string s and the target string t.