diff --git a/memo.md b/memo.md
index efb0777..d5996bb 100644
--- a/memo.md
+++ b/memo.md
@@ -2,12 +2,161 @@
 
 ## アプローチ
 
+* `sr`, `sc`をスタートとして, 隣接する色が同じセルを`color`に変えていく
+* BFSまたはDFSでできる
+* BFSの方がより現実の動作に近いからBFSで実装する
+* 再帰でもループでもいいが練習のためループで実装する
+* 全部のセルを見る場合が最大の実行時間になる
+    * 50 * 50 / 10^6 ~= 10^-3 sec程度
+* 2:50
+
 ## Code1-1
 
+* 8:02
+
+```python
+import copy
+
+
+class Solution:
+    def floodFill(self, image: List[List[int]], sr: int, sc: int, color: int) -> List[List[int]]:
+        image = copy.deepcopy(image)
+
+        num_rows = len(image)
+        num_cols = len(image[0])
+        if (sr < 0 or num_rows <= sr) or (sc < 0 or num_cols <= sc):
+            return image
+
+        original_color = image[sr][sc]
+
+        frontier = [(sr, sc)]
+        visited = set()
+        while frontier:
+            next_frontier = []
+            for r, c in frontier:
+                visited.add((r, c))
+                image[r][c] = color
+                for dr, dc in [(1, 0), (0, 1), (-1, 0), (0, -1)]:
+                    new_r = r + dr
+                    new_c = c + dc
+                    if (new_r < 0 or num_rows <= new_r) or (new_c < 0 or num_cols <= new_c):
+                        continue
+                    if (new_r, new_c) in visited:
+                        continue
+                    if image[new_r][new_c] != original_color:
+                        continue
+                    next_frontier.append((new_r, new_c))
+            frontier = next_frontier
+        
+        return image
+        
+```
+
 # Step2
 
 ## Code2-1
 
+* 範囲に入っているかどうかの判定を関数に切り出した
+
+```python
+import copy
+
+
+class Solution:
+    def floodFill(self, image: List[List[int]], sr: int, sc: int, color: int) -> List[List[int]]:
+        def is_in_image(row: int, col: int):
+            if row < 0 or num_rows <= row:
+                return False
+            if col < 0 or num_cols <= col:
+                return False
+            return True
+
+        image = copy.deepcopy(image)
+
+        num_rows = len(image)
+        num_cols = len(image[0])
+        if not is_in_image(sr, sc):
+            return image
+
+        original_color = image[sr][sc]
+
+        frontier = [(sr, sc)]
+        visited = set()
+        while frontier:
+            next_frontier = []
+            for r, c in frontier:
+                visited.add((r, c))
+                image[r][c] = color
+                for dr, dc in [(1, 0), (0, 1), (-1, 0), (0, -1)]:
+                    new_r = r + dr
+                    new_c = c + dc
+                    if not is_in_image(new_r, new_c):
+                        continue
+                    if (new_r, new_c) in visited:
+                        continue
+                    if image[new_r][new_c] != original_color:
+                        continue
+                    next_frontier.append((new_r, new_c))
+            frontier = next_frontier
+        
+        return image
+        
+```
+
+## 他の解法を見る
+
+* 再帰(dfs)が多かった
+
 # Step3
 
 ## Code3-1
+
+* 6:09
+* 4:33
+* 3:07
+
+```python
+import copy
+
+
+class Solution:
+    def floodFill(self, image: List[List[int]], sr: int, sc: int, color: int) -> List[List[int]]:
+        image_copy = copy.deepcopy(image)
+
+        num_rows = len(image_copy)
+        num_cols = len(image_copy[0])
+
+        def is_in_image(row: int, col: int) -> bool:
+            if row < 0 or num_rows <= row:
+                return False
+            if col < 0 or num_cols <= col:
+                return False
+            return True
+        
+        if not is_in_image(sr, sc):
+            return image_copy
+        
+        original_color = image_copy[sr][sc]
+
+        coordinates = [(sr, sc)]
+        visited = set()
+        while coordinates:
+            next_coordinates = []
+            for r, c in coordinates:
+                visited.add((r, c))
+                image_copy[r][c] = color
+                for dr, dc in [(1, 0), (0, 1), (-1, 0), (0, -1)]:
+                    new_r = r + dr
+                    new_c = c + dc
+                    if not is_in_image(new_r, new_c):
+                        continue
+                    if (new_r, new_c) in visited:
+                        continue
+                    if image_copy[new_r][new_c] != original_color:
+                        continue
+                    next_coordinates.append((new_r, new_c))
+            coordinates = next_coordinates
+
+        return image_copy
+
+```