What are the best coding challenges to learn sorting algorithms?

2 Merge Sort

Merge sort is a divide-and-conquer algorithm that splits an array into smaller subarrays, sorts them recursively, and then merges them back together. It is faster and more stable than bubble sort, but it requires extra space. The challenge is to implement merge sort in any programming language of your choice, and compare its performance with bubble sort. You'll learn how to use recursion, merging, and splitting, and how to handle edge cases and errors.

4 Counting Sort

Counting sort is a non-comparative algorithm that sorts an array of integers by counting the frequency of each value, and then outputting them in order. It is very fast and stable, but it only works for a limited range of values. The challenge is to implement counting sort in any programming language of your choice, and apply it to different types of data, such as strings or objects. You'll learn how to use arrays, counters, and indices, and how to adapt your algorithm for different scenarios.

5 Radix Sort

Radix sort is another non-comparative algorithm that sorts an array of integers by sorting them digit by digit, from the least significant to the most significant. It uses a stable sorting algorithm, such as counting sort, as a subroutine. It is very efficient for large numbers, but it requires extra space and arithmetic operations. The challenge is to implement radix sort in any programming language of your choice, and analyze its time and space complexity. You'll learn how to use base conversion, digit extraction, and stable sorting, and how to handle negative numbers and decimals.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?