diff --git a/HashMap.java b/HashMap.java
new file mode 100644
index 00000000..ec40757c
--- /dev/null
+++ b/HashMap.java
@@ -0,0 +1,36 @@
+// Time Complexity : O(1) for put, O(1) for get and remove
+// Space Complexity : O(n) where n is the number of key-value pairs in the hash map
+// Did this code successfully run on Leetcode : Yes
+// Any problem you faced while coding this : 
+// this approach initializes an array of size 1000001 to store the values, 
+// which may not be the most space-efficient solution if the number of key-value pairs is small. 
+// However, it provides O(1) time complexity for put, get, and remove operations.
+
+
+// This approach uses a simple array to implement the hash map. 
+// We initialize an array of size 1000001 to store the values, 
+// and fill it with -1 to indicate that the key is not present. 
+// The put method updates the value at the index corresponding to the key, 
+// the get method returns the value at the index corresponding to the
+
+import java.util.Arrays;
+
+class MyHashMap {
+    int[] map;
+    public MyHashMap() {
+        map = new int[1000001];
+        Arrays.fill(map, -1);
+    }
+    
+    public void put(int key, int value) {
+        map[key] = value;
+    }
+    
+    public int get(int key) {
+        return map[key];
+    }
+    
+    public void remove(int key) {
+        map[key] = -1;
+    }
+}
\ No newline at end of file
diff --git a/QueueWithStacks.java b/QueueWithStacks.java
new file mode 100644
index 00000000..46084d57
--- /dev/null
+++ b/QueueWithStacks.java
@@ -0,0 +1,50 @@
+// Time Complexity : O(1) for push, O(n) for pop and peek in worst case when outStack is empty, O(1) for pop and peek in average case when outStack is not empty
+// Space Complexity : O(n) where n is the number of elements in the queue
+// Did this code successfully run on Leetcode : Yes
+// Any problem you faced while coding this :
+
+
+// this approach uses two stacks to implement a queue. 
+// The inStack is used to store the elements when they are pushed into the queue, 
+// and the outStack is used to store the elements when they are popped from the queue. 
+// When we need to pop or peek an element, we check if the outStack is empty. 
+// If it is empty, we transfer all elements from the inStack to the outStack, 
+// which reverses the order of the elements and allows us to access the front of the queue. 
+// If the outStack is not empty, we can directly pop or peek from it. 
+// This way, we maintain the FIFO order of the queue using two LIFO stacks.
+
+import java.util.Stack;
+
+class MyQueue {
+    Stack<Integer> inStack;
+    Stack<Integer> outStack;
+    public MyQueue() {
+        inStack = new Stack<Integer>();
+        outStack = new Stack<Integer>();
+    }
+    
+    public void push(int x) {
+        inStack.push(x);
+    }
+    
+    public int pop() {
+        if(empty()){
+            return -1;
+        }
+        peek();
+        return outStack.pop();
+    }
+    
+    public int peek() {
+        if(outStack.isEmpty()){
+            while(!inStack.isEmpty()){
+                outStack.push(inStack.pop());
+            }
+        }
+        return outStack.peek();
+    }
+    
+    public boolean empty() {
+        return inStack.isEmpty() && outStack.isEmpty();
+    }
+}
\ No newline at end of file
diff --git a/Sample.java b/Sample.java
deleted file mode 100644
index 1739a9cb..00000000
--- a/Sample.java
+++ /dev/null
@@ -1,7 +0,0 @@
-// Time Complexity :
-// Space Complexity :
-// Did this code successfully run on Leetcode :
-// Any problem you faced while coding this :
-
-
-// Your code here along with comments explaining your approach