What are data structures?

Data structures are basically a way to organize data. They’re mathematical models for organizing information. Their main goal is to take the input, sort it and present it back in an easy to understand format that can be used by other computer programs or humans. This then becomes the API that other software interfaces with. The API should be well documented, flexible enough for future changes, reliable and maintainable.

What are algorithms?

Algorithms are step-by-step instructions which give the necessary commands to solve a problem or attain an objective efficiently. Algorithms can be implemented as subroutines in programming languages or standalone applications but they don’t have to necessarily relate code at all – It could just be a sequence of events.

Top 10 Algorithms and why they are useful

1) Bubble Sort

Bubble sort is an efficient sorting algorithm that works by repeatedly stepping through the list to be sorted, compares each pair of adjacent items and swaps them if they are in the wrong order . It then steps again and repeats until no swaps are needed, which indicates that the list is sorted.

Why is bubble sort useful?

The algorithm has O(n2) average time complexity which means that it scales very badly for large lists (>100 elements). If you have a small number of records to sift through, this may not concern you but for most practical cases it’s more favourable to use one of the many other sorting algorithms.

2) Selection Sort

Selection sort works by finding the smallest (or largest, depending on how it is implemented) element in a list and swapping it with the first element. Then it finds the second smallest and swaps it with the second element, continuing until all elements have been swapped to their correct location .

Why is selection sort useful?

This type of sorting algorithm has a O(n2) time complexity which means that it scales very badly for large lists (>100 elements). If you have a small number of records to sift through, this may not concern you but for most practical cases it’s more favourable to use one of the other simpler sorts instead.

3) Insertion Sort

Insertion sort works by considering the first element of an unsorted list and adding it to its correct place in a sorted list. It then considers the second element in the unsorted list, finds where that element should go in the sorted list, and inserts it there . The algorithm continues this process for each subsequent element until all elements are inserted into their correct location .

Why is Insertion sort useful?

This type of sorting algorithm has O(n2) time complexity which means that it scales very badly for large lists (>100 elements). If you have a small number of records to sift through, this may not concern you but for most practical cases it’s more favourable to use one of the simpler sorts instead.

4) Merge Sort

Merge sort is a sorting algorithm that splits the list into two parts, sorts each part and then merges the two sorted lists back together .

Why is merge sort useful?

This type of sorting algorithm has O(nlogn) time complexity which means that it scales very well for large lists (>100 elements). It’s one of the most efficient sorts available and is commonly used in practice.

5) Quick Sort

Quick sort is a sorting algorithm that works by partitioning the list into two smaller lists, one of which contains all items that are less than the pivot element and the other contains all items that are greater than or equal to the pivot element. The algorithm then recursively calls quick sort on these two lists .

Why is quick sort useful?

This type of sorting algorithm has O(nlogn) time complexity which means that it scales very well for large lists (>100 elements). It’s one of the most efficient sorts available and is commonly used in practice.

6) Heap Sort

Heap sort is a sorting algorithm that builds a heap (a special type of binary tree) from the list to be sorted and then uses the heap’s “heapify” function to gradually swap elements into their correct location .

Why is heap sort useful?

This type of sorting algorithm has an O(nlogn) time complexity which means that it scales very well for large lists (>100 elements). It’s less commonly used than some of the other algorithms but can be more efficient in some cases.

7) Counting Sort

Counting sort is a sorting algorithm that counts the number of items that are less than or greater than a given value and then sorts the list based on those counts .

Why is counting sort useful?

This type of sorting algorithm has O(n) time complexity which means that it’s very efficient for small lists (<100 elements). It’s not commonly used in practice but can be useful in some situations.

8) Radix Sort

Radix sort is a sorting algorithm that works by considering each digit of an integer separately and sorting them in ascending order .

Why is radix sort useful?

This type of sorting algorithm has O(n) time complexity which means that it’s very efficient for small lists (<100 elements). It’s not commonly used in practice but can be useful in some situations.

9) Shell Sort

Shell sort is a sorting algorithm that considers each digit individually and sorts them in descending order . It then uses the previously sorted digits to determine where subsequent digits should go . If you like, you can think of it as working backwards from the end of a number (or list) to its start .

Why is shell sort useful? Shell sort works by taking advantage of the fact that smaller numbers take less time to search than larger numbers. This type of sorting algorithm has O(nlogn)

10) Counting Insertion Sort

Counting insertion sort was covered briefly in an earlier section but this time, we’ll take a look at how it works . The algorithm works by keeping track of how many items are less than or greater than a given value . It then repeatedly counts down from the maximum value until reaching the middle of the list, inserting each item into its correct location as it goes along .

Why is counting insertion sort useful?

This type of sorting algorithm has O(n) time complexity which means that it’s very efficient for small lists (<100 elements).What are data structures?