arrange in proper order

Author: PallavJain01

Sort Array 0-1-2.md

@@ -1,48 +1,19 @@
 ### [Back2Home](https://github.com/CodingWallah/Arrays-DSA-Coding-Questions) | [Go2Video](#)
 
+##
 
+### Solution 1 `Not Recommended`
+#### Time Complexity: `O(n*logn)`
 
-### Solution 1 `Best`
-#### Time Complexity: `O(n)`
-#### Space Complexity: `O(1)`
 ```java
-
 class Solution {
  public void sortColors(int[] nums) {
- int start = 0;
- int end = nums.length - 1;
- int ptr = 0, temp = 0;
-
- while (ptr <= end) {
- switch (nums[ptr]) {
- case 0: {
- temp = nums[start];
- nums[start] = nums[ptr];
- nums[ptr] = temp;
- start++;
- ptr++;
- break;
- }
- case 1: {
- ptr++;
- break;
- }
- case 2: {
- temp = nums[ptr];
- nums[ptr] = nums[end];
- nums[end] = temp;
- end--;
- break; 
- }
- }
- }
+ Arrays.sort(nums);
  }
 }
 ```
 
-##
-
-### Solution 2
+### Solution 2 `Alternative`
 #### Time Complexity: `O(n)`
 #### Space Complexity: `O(1)`
 ```java
@@ -77,15 +48,43 @@ class Solution {
  }
  }
 }
-
 ```
-### Solution 3 `Not Recommended`
-#### Time Complexity: `O(n*logn)`
+
+### Solution 3 `Best`
+#### Time Complexity: `O(n)`
+#### Space Complexity: `O(1)`
 
 ```java
+
 class Solution {
  public void sortColors(int[] nums) {
- Arrays.sort(nums);
+ int start = 0;
+ int end = nums.length - 1;
+ int ptr = 0, temp = 0;
+
+ while (ptr <= end) {
+ switch (nums[ptr]) {
+ case 0: {
+ temp = nums[start];
+ nums[start] = nums[ptr];
+ nums[ptr] = temp;
+ start++;
+ ptr++;
+ break;
+ }
+ case 1: {
+ ptr++;
+ break;
+ }
+ case 2: {
+ temp = nums[ptr];
+ nums[ptr] = nums[end];
+ nums[end] = temp;
+ end--;
+ break; 
+ }
+ }
+ }
  }
 }
-```
+```

kth-largest-smallest.md

@@ -13,6 +13,7 @@
 
 ### Solution 1 : Using Sorting
 #### Time Complexity: `O(n*logn)`
+`Not Recommended`
 ```java
 class Solution {
  public int findKthLargest(int[] nums, int k) {
@@ -26,6 +27,20 @@ class Solution {
 
 ### Solution 2: Min Heap Approach 
 #### Time Complexity: `O(n + n*logk)`
+
+`Concise Implementation`
+
+```java
+PriorityQueue<Integer> pq = new PriorityQueue<Integer>(); 
+ for(int i : nums){
+ pq.add(i);
+ if(pq.size()>k){
+ pq.remove();
+ }
+ }
+return pq.remove();
+```
+
 `Best Solution`
 ```java
 PriorityQueue<Integer> minheap = new PriorityQueue<Integer>();
@@ -41,23 +56,24 @@ PriorityQueue<Integer> minheap = new PriorityQueue<Integer>();
 return minheap.peek();
 ```
 
-`Concise Implementation`
 
+## 
+
+### Solution 3: Max Heap Approach
+#### Time Complexity: `O(n + n*logk)` 
+
+`Consice Implementation`
 ```java
-PriorityQueue<Integer> pq = new PriorityQueue<Integer>(); 
+PriorityQueue<Integer> pq = new PriorityQueue<Integer>(Collections.reverseOrder());  
  for(int i : nums){
  pq.add(i);
- if(pq.size()>k){
-  pq.remove();
- }
- }
-return pq.remove();
+  
+ for(int i=1;i<k;i++)
+ pq.poll();
+ 
+return pq.peek(); 
 ```
 
-## 
-
-### Solution 3: Max Heap Approach
-#### Time Complexity: `O(n + n*logk)`
 `Best Solution`
 ```java
 PriorityQueue<Integer> maxHeap = new PriorityQueue<Integer>(Collections.reverseOrder()); 
@@ -71,16 +87,4 @@ PriorityQueue<Integer> maxHeap = new PriorityQueue<Integer>(Collections.reverseO
  }
  }
 return maxHeap.peek();
-```
-
-`Consice Implementation`
-```java
-PriorityQueue<Integer> pq = new PriorityQueue<Integer>(Collections.reverseOrder()); 
- for(int i : nums){
- pq.add(i);
- 
- for(int i=1;i<k;i++)
- pq.poll();
- 
-return pq.peek(); 
-```
+```