We provide you with some algo codes and following are commonly steps used by us in algorithm development:

1. Algorithm: A set of instructions that a computer follows to solve a problem.
2. Data structure: A way of organizing and storing data in a computer program, such as an array, linked list, or hash table.
3. Complexity: The amount of time or space required to run an algorithm as a function of its input size.
4. Optimization: The process of improving an algorithm’s efficiency by reducing its time or space complexity.
5. Big O notation: A mathematical notation used to describe the time or space complexity of an algorithm as a function of its input size.
6. Recursion: A programming technique where a function calls itself to solve a problem.
7. Dynamic programming: A programming technique that solves a problem by breaking it down into smaller subproblems and solving them recursively.
8. Greedy algorithm: An algorithm that makes locally optimal choices at each step in order to find a global optimum.
9. Search algorithm: An algorithm that finds a specific item in a collection of items, such as a binary search or linear search.
10. Sorting algorithm: An algorithm that arranges a collection of items in a specific order, such as bubble sort, quicksort, or merge sort.