14 Coding Patterns to Solve DSA (Part 2)

Continuing the Journey: 7 More Coding Patterns to Strengthen Your DSA Skills

Photo by Joshua Reddekopp on Unsplash

In the first part, we covered seven essential coding patterns. Now, let's continue with the remaining seven patterns that are crucial for solving DSA problems efficiently. Each pattern is accompanied by a code template and a list of similar problems for practice.

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8. Divide and Conquer Pattern

Algorithm:

• Divide and Conquer is a powerful algorithmic technique that divides a problem into smaller subproblems, solves the subproblems independently, and combines the results to solve the original problem. This technique is commonly used in problems that can be broken down recursively.

Similar Problems:

1. Merge Sort
2. Quick Sort
3. Binary Search

Code Template:

public class DivideAndConquer {
    public int[] mergeSort(int[] nums) {
        if (nums.length <= 1) return nums;
        
        int mid = nums.length / 2;
        int[] left = Arrays.copyOfRange(nums, 0, mid);
        int[] right = Arrays.copyOfRange(nums, mid, nums.length);
        
        return merge(mergeSort(left), mergeSort(right));
    }
    
    private int[] merge(int[] left, int[] right) {
        int[] result = new int[left.length + right.length];
        int i = 0, j = 0, k = 0;
        
        while (i < left.length && j < right.length) {
            if (left[i] <= right[j]) {
                result[k++] = left[i++];
            } else {
                result[k++] = right[j++];
            }
        }
        
        while (i < left.length) result[k++] = left[i++];
        while (j < right.length) result[k++] = right[j++];
        
        return result;
    }
}

9. Dynamic Programming (DP) Pattern

Algorithm:

• Dynamic Programming (DP) is a technique used to solve optimization problems by breaking them down into simpler subproblems. DP uses memoization or tabulation to store the results of subproblems to avoid redundant calculations, thereby optimizing the…