diff --git a/0215.Kth-Largest-Element-in-an-Array/memo.md b/0215.Kth-Largest-Element-in-an-Array/memo.md
new file mode 100644
index 0000000..3473c80
--- /dev/null
+++ b/0215.Kth-Largest-Element-in-an-Array/memo.md
@@ -0,0 +1,38 @@
+# 215. Kth Largest Element in an Array
+
+## step1
+
+heapを使った解法を思いつく。3minほど。
+
+heappushpopを使った場合も書いた。
+
+heapreplaceというメソッドもあるが今回は使わない。
+
+## step2
+
+Mediumとなっていることから考えて、本来の出題意図はQuick Selectを書かせたいのではないだろうか。
+
+愚直に書くとTLEしたので、pivotの最初と終わりを返すようにした。
+
+かなり時間がかかってしまった（測り忘れた）。添字と長さで混乱し、手で具体例を書いて添字を合わせた。
+
+以下の問題のアルゴリズム（Dutch National Flag）に似ている。
+
+https://leetcode.com/problems/sort-colors/description/?envType=problem-list-v2&envId=rab78cw1
+
+Arai60の問題:
+
+https://leetcode.com/problems/kth-largest-element-in-a-stream/description/
+
+解くだけなら今回の問題の方が簡単だがQuick Selectを書くのが大変。
+
+書き直したら分かりやすくなった。
+
+## step3
+
+Quick selectを書く。
+
+間違えた点：
+
+- left == rightの場合の処理（これがないと無限ループ）
+- dutch flagのwhileの条件を<とした
diff --git a/0215.Kth-Largest-Element-in-an-Array/step1_heap.py b/0215.Kth-Largest-Element-in-an-Array/step1_heap.py
new file mode 100644
index 0000000..35c9806
--- /dev/null
+++ b/0215.Kth-Largest-Element-in-an-Array/step1_heap.py
@@ -0,0 +1,24 @@
+import heapq
+
+
+class Solution:
+    def findKthLargest(self, nums: list[int], k: int) -> int:
+        heap = []
+        for n in nums:
+            heapq.heappush(heap, n)
+            if len(heap) > k:
+                heapq.heappop(heap)
+
+        return heapq.heappop(heap)
+
+
+class Solution:
+    def findKthLargest(self, nums: list[int], k: int) -> int:
+        heap = []
+        for n in nums:
+            if len(heap) == k:
+                heapq.heappushpop(heap, n)
+            else:
+                heapq.heappush(heap, n)
+
+        return heapq.heappop(heap)
diff --git a/0215.Kth-Largest-Element-in-an-Array/step2_quick_select.py b/0215.Kth-Largest-Element-in-an-Array/step2_quick_select.py
new file mode 100644
index 0000000..1faa6ac
--- /dev/null
+++ b/0215.Kth-Largest-Element-in-an-Array/step2_quick_select.py
@@ -0,0 +1,43 @@
+import random
+
+random.seed(42)
+
+
+class Solution:
+    def findKthLargest(self, nums: list[int], k: int) -> int:
+        def partition(pivot_index, left, right):
+            if left == right:
+                return nums[left]
+
+            pivot_value = nums[pivot_index]
+            end_of_smaller = left
+            end_of_pivot = right
+            i = left
+            while i <= end_of_pivot:
+                if nums[i] < pivot_value:
+                    nums[i], nums[end_of_smaller] = nums[end_of_smaller], nums[i]
+                    end_of_smaller += 1
+                    i += 1
+                elif nums[i] > pivot_value:
+                    nums[i], nums[end_of_pivot] = nums[end_of_pivot], nums[i]
+                    end_of_pivot -= 1
+                else:
+                    i += 1
+
+            return end_of_smaller, end_of_pivot
+
+        def quick_select(left, right, l):
+            if left == right:
+                return nums[left]
+            pivot_index = random.randint(left, right)
+            end_of_smaller, end_of_pivot = partition(pivot_index, left, right)
+            if right + 1 - end_of_pivot < l <= right + 1 - end_of_smaller:
+                return nums[end_of_smaller]
+            elif right + 1 - end_of_pivot < l:
+                return quick_select(
+                    left, end_of_smaller - 1, l - (right + 1 - end_of_smaller)
+                )
+            else:  # l <= right + 1 - end_of_pivot
+                return quick_select(end_of_pivot, right, l)
+
+        return quick_select(0, len(nums) - 1, k)
diff --git a/0215.Kth-Largest-Element-in-an-Array/step2_quick_select_revised.py b/0215.Kth-Largest-Element-in-an-Array/step2_quick_select_revised.py
new file mode 100644
index 0000000..c85bc5e
--- /dev/null
+++ b/0215.Kth-Largest-Element-in-an-Array/step2_quick_select_revised.py
@@ -0,0 +1,43 @@
+import random
+
+random.seed(42)
+
+
+class Solution:
+    def findKthLargest(self, nums: list[int], k: int) -> int:
+        def partition(pivot_index, left, right):
+            if left == right:
+                return nums[left]
+
+            pivot_value = nums[pivot_index]
+            end_of_smaller = left
+            end_of_pivot = right
+            i = left
+            while i <= end_of_pivot:
+                if nums[i] < pivot_value:
+                    nums[i], nums[end_of_smaller] = nums[end_of_smaller], nums[i]
+                    end_of_smaller += 1
+                    i += 1
+                elif nums[i] > pivot_value:
+                    nums[i], nums[end_of_pivot] = nums[end_of_pivot], nums[i]
+                    end_of_pivot -= 1
+                else:
+                    i += 1
+
+            return end_of_smaller, end_of_pivot
+
+        target_index = len(nums) - k
+
+        def quick_select(left, right):
+            if left == right:
+                return nums[left]
+            pivot_index = random.randint(left, right)
+            end_of_smaller, end_of_pivot = partition(pivot_index, left, right)
+            if end_of_smaller <= target_index < end_of_pivot:
+                return nums[end_of_smaller]
+            elif target_index < end_of_smaller:
+                return quick_select(left, end_of_smaller - 1)
+            else:  # end_of_pivot <= target_index
+                return quick_select(end_of_pivot, right)
+
+        return quick_select(0, len(nums) - 1)
diff --git a/0215.Kth-Largest-Element-in-an-Array/step2_quick_select_tle.py b/0215.Kth-Largest-Element-in-an-Array/step2_quick_select_tle.py
new file mode 100644
index 0000000..4d80760
--- /dev/null
+++ b/0215.Kth-Largest-Element-in-an-Array/step2_quick_select_tle.py
@@ -0,0 +1,36 @@
+import random
+
+random.seed(42)
+
+
+class Solution:
+    def findKthLargest(self, nums: list[int], k: int) -> int:
+        def partition(pivot_index, left, right):
+            if left == right:
+                return nums[left]
+
+            nums[pivot_index], nums[right] = nums[right], nums[pivot_index]
+            end_of_smaller = left
+            for i in range(left, right):
+                if nums[i] <= nums[right]:
+                    nums[i], nums[end_of_smaller] = nums[end_of_smaller], nums[i]
+                    end_of_smaller += 1
+
+            nums[end_of_smaller], nums[right] = nums[right], nums[end_of_smaller]
+            return end_of_smaller
+
+        def quick_select(left, right, l):
+            if left == right:
+                return nums[left]
+            pivot_index = random.randint(left, right)
+            partitioned_index = partition(pivot_index, left, right)
+            if right - partitioned_index == l - 1:
+                return nums[partitioned_index]
+            elif right - partitioned_index < l - 1:
+                return quick_select(
+                    left, partitioned_index - 1, l - (right - partitioned_index + 1)
+                )
+            else:
+                return quick_select(partitioned_index + 1, right, l)
+
+        return quick_select(0, len(nums) - 1, k)
diff --git a/0215.Kth-Largest-Element-in-an-Array/step3_quick_select.py b/0215.Kth-Largest-Element-in-an-Array/step3_quick_select.py
new file mode 100644
index 0000000..a715127
--- /dev/null
+++ b/0215.Kth-Largest-Element-in-an-Array/step3_quick_select.py
@@ -0,0 +1,43 @@
+from math import e
+import random
+
+random.seed(42)
+
+
+class Solution:
+    def findKthLargest(self, nums: list[int], k: int) -> int:
+        def partition(pivot_index, left, right):
+            pivot = nums[pivot_index]
+            end_of_smaller = left
+            end_of_pivot = right
+            index = left
+            while index <= end_of_pivot:
+                if nums[index] < pivot:
+                    nums[index], nums[end_of_smaller] = (
+                        nums[end_of_smaller],
+                        nums[index],
+                    )
+                    index += 1
+                    end_of_smaller += 1
+                elif nums[index] == pivot:
+                    index += 1
+                else:
+                    nums[index], nums[end_of_pivot] = nums[end_of_pivot], nums[index]
+                    end_of_pivot -= 1
+            return end_of_smaller, end_of_pivot
+
+        target_index = len(nums) - k
+
+        def quick_select(left, right):
+            if left == right:
+                return nums[left]
+            pivot_index = random.randint(left, right)
+            end_of_smaller, end_of_pivot = partition(pivot_index, left, right)
+            if target_index < end_of_smaller:
+                return quick_select(left, end_of_smaller - 1)
+            elif target_index >= end_of_pivot:
+                return quick_select(end_of_pivot, right)
+            else:
+                return nums[end_of_smaller]
+
+        return quick_select(0, len(nums) - 1)