Array

We can use following major approaches to solve array related problem:

1. Iterative Approach: This is a straightforward method where you loop over the elements in the array one by one, performing some operation on each element. It’s often used when you need to process each element in the array individually or when the order of processing doesn’t matter.

2. Two-Pointer Approach: This technique involves maintaining two pointers into the array and moving them to solve the problem. The pointers can either move in the same direction (e.g., in a sliding window approach) or in opposite directions (e.g., when searching for a pair of elements that sum to a target value). This approach is often used when the problem involves pairs of elements or a subarray of elements.

3. Sliding Window: This is a variant of the two-pointer approach where the pointers represent the start and end of a “window” into the array. The window “slides” over the array by moving the pointers. This approach is often used when the problem involves a subarray of elements and has a condition involving the sum or product of the elements in the subarray.

4. Dynamic Sliding Window: This is a variant of the sliding window approach where the size of the window can change dynamically based on certain conditions. For example, you might expand the window when the sum of the elements in the window is less than a target value and shrink the window when the sum is greater than the target.

5. Hashing: This technique involves using a hash table (like a dictionary in C#) to store elements of the array for quick lookup. It’s often used when you need to find if an array contains a certain element or when you need to count the occurrences of elements.

6. Dynamic Programming: This is a method for solving complex problems by breaking them down into simpler subproblems and solving each subproblem only once, storing their results to avoid duplicate work. It’s often used when the problem involves making a sequence of decisions or when the problem can be broken down into overlapping subproblems.

7. Recursion: This involves breaking down the problem into smaller subproblems that are similar to the original problem. This approach is useful for problems that have a recursive structure.

Each of these techniques has its own strengths and is suited to different types of problems. The key to choosing the right technique is understanding the nature of the problem and the properties of the array you’re working with.