diff --git a/problem1.py b/problem1.py
new file mode 100644
index 00000000..79986c81
--- /dev/null
+++ b/problem1.py
@@ -0,0 +1,17 @@
+#Find Missing Number in a sorted array
+# Provide an array of n-1 integers in the range of 1 to n with no duplicates in list,
+# One of the integers is missing in the list. Write a code to find the missing integer.
+def search(arr):
+    l=0
+    r=len(arr)-1
+    # Trying to make the binary search stop when both and l are equal
+    while l<r:
+        m=l+(r-l)//2
+        # If it is true then until that point, numbers are in correct position, must be on right side
+        if arr[m] == m+1:
+            l=m+1
+        #must be on left side including middle
+        else:
+            r=m
+    return l+1
+        
\ No newline at end of file
diff --git a/problem2.py b/problem2.py
new file mode 100644
index 00000000..ef966901
--- /dev/null
+++ b/problem2.py
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+class MinHeap:
+    def __init__(self):
+        self.minheap = []
+    
+    def getMin(self):
+        if not self.minheap:
+            return None
+        return self.minheap[0]
+
+    def insert(self, val):
+        self.minheap.append(val)
+        index = len(self.minheap) - 1
+
+        # heapify up
+        # Swapping parent and current element until it is less than parent
+        # As parent needs to be the smallest of all children
+        while index > 0:
+            parent = (index - 1) // 2
+            if self.minheap[index] < self.minheap[parent]:
+                self.minheap[index], self.minheap[parent] = self.minheap[parent], self.minheap[index]
+                index = parent
+            else:
+                break
+
+    def extractMin(self):
+        # If there are no elements return None
+        if not self.minheap:
+            return None
+
+        # since the root is always the minimum value swap the root with the last value
+        # remove the min value and store it to return later after we correct the heap
+        self.minheap[0], self.minheap[-1] = self.minheap[-1], self.minheap[0]
+        min_val = self.minheap.pop()
+
+        index = 0
+        n = len(self.minheap)
+
+
+        # B/w the parent and its children find out which is the smallest and swap
+       
+        while True:
+            l = 2*index + 1
+            r = 2*index + 2
+            smallest = index
+
+            if l < n and self.minheap[l] < self.minheap[smallest]:
+                smallest = l
+            if r < n and self.minheap[r] < self.minheap[smallest]:
+                smallest = r
+            # If the parent is already the smallest among the children heap property is already satisfied 
+            if smallest == index:
+                break
+            # If not, swap the parent with the minimum of the 2 children
+            self.minheap[index], self.minheap[smallest] = self.minheap[smallest], self.minheap[index]
+            index = smallest
+
+        return min_val
+