diff --git a/Problem1.py b/Problem1.py
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index 0000000..0921d0a
--- /dev/null
+++ b/Problem1.py
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+# Time Complexity --> O(m*n) will be the amortized complexity. As the number of initial rotten oranges increases, the number of times revisiting an orange will decrease since the distance increases. 
+# Space Complexity --> O(m*n)
+class Solution:
+    def orangesRotting(self, grid: List[List[int]]) -> int:
+        m = len(grid)
+        n = len(grid[0])
+        self.dirs = [(0,1),(1,0),(0,-1),(-1,0)]
+        for i in range(m):
+            for j in range(n):
+                if grid[i][j]==2:
+                    self.dfs(grid, i, j, 2) 
+        
+        maxi = 2
+        for i in range(m):
+            for j in range(n):
+                if grid[i][j]==1:
+                    return -1
+                maxi = max(maxi, grid[i][j])
+        return maxi-2
+        
+    
+    def dfs(self, grid, r, c, time):
+        #base 
+        if r<0 or c<0 or r==len(grid) or c==len(grid[0]):
+            return
+        if grid[r][c]!=1 and grid[r][c]<time:
+            return
+
+        #logic
+        grid[r][c] = time 
+        for dir in self.dirs:
+            nr = r + dir[0]
+            nc = c + dir[1]
+            self.dfs(grid, nr, nc, time+1)
+
+
+
+
+
+'''
+# Time Complexity --> O(m*n)
+# Space Complexity --> O(m*n)
+
+from collections import deque
+class Solution:
+    def orangesRotting(self, grid: List[List[int]]) -> int:
+        q = deque()
+        m = len(grid)
+        n = len(grid[0])
+        fresh = 0
+
+        for i in range(m):
+            for j in range(n):
+                if grid[i][j]==2:
+                    q.append((i,j))
+                elif grid[i][j]==1:
+                    fresh += 1
+        
+        if len(q)==0 and fresh==0:
+            return 0
+
+        dirs = [(0,1),(1,0),(0,-1),(-1,0)]
+        time = 0
+        while len(q)>0:
+            size = len(q)
+            for i in range(size):
+                curr = q.popleft()
+                for dir in dirs:
+                    nr = curr[0] + dir[0]
+                    nc = curr[1] + dir[1]
+                    if nr>=0 and nr<m and nc>=0 and nc<n and grid[nr][nc]==1:
+                        q.append((nr,nc))
+                        grid[nr][nc] = 2
+                        fresh -= 1
+            time += 1
+        
+        if fresh>0:
+            return -1
+        return time-1
+
+'''
diff --git a/Problem2.py b/Problem2.py
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+++ b/Problem2.py
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+"""
+# Definition for Employee.
+class Employee:
+    def __init__(self, id: int, importance: int, subordinates: List[int]):
+        self.id = id
+        self.importance = importance
+        self.subordinates = subordinates
+"""
+# Time Complexity --> O(n)
+# Space Complexity --> O(n)
+# Approach --> DFS
+class Solution:
+    def getImportance(self, employees: List['Employee'], id: int) -> int:
+        hmap = {}
+        for emp in employees:
+            hmap[emp.id] = emp
+        self.result = 0
+        self.dfs(id, hmap)
+        return self.result
+    
+    def dfs(self, id, hmap):
+        self.result += hmap[id].importance
+        for subordinate in hmap[id].subordinates:
+            self.dfs(subordinate, hmap)
+
+
+'''
+# Time Complexity --> O(n)
+# Space Complexity --> O(n)
+# Approach --> BFS
+class Solution:
+    def getImportance(self, employees: List['Employee'], id: int) -> int:
+        hmap = {}
+        for e in employees:
+            hmap[e.id] = e
+        q = deque()
+        q.append(id)
+        result = 0
+        while len(q)>0:
+            currid = q.popleft()
+            curremp = hmap[currid]
+            result += curremp.importance
+            for subordinate in curremp.subordinates:
+                q.append(subordinate)
+        return result 
+'''