feat: refactored docs structure

docs/(05-decision-space)/backtracking/(problems)/78_subsets.mdx

@@ -0,0 +1,45 @@
+---
+title: '78. Subsets'
+description: Given an integer array nums of unique elements, return all possible subsets (the power set)
+icon: dot
+topics:
+  - { name: "Array", slug: "array" }
+  - { name: "Backtracking", slug: "backtracking" }
+  - { name: "Bit Manipulation", slug: "bit-manipulation" }
+issue: "https://github.com/prdlk/leetcode/issues/149"
+sidebar:
+  label: 'Subsets'
+  badge: 'Medium'
+---
+
+### Example 1:
+- Input: `nums = [1,2,3]`
+- Output: `[[],[1],[2],[1,2],[3],[1,3],[2,3],[1,2,3]]`
+
+### Example 2:
+- Input: `nums = [0]`
+- Output: `[[],[0]]`
+
+### Constraints:
+
+- `1 <= nums.length <= 10`
+- `-10 <= nums[i] <= 10`
+- All the numbers of `nums` are unique.
+
+## Solution
+
+```py
+class Solution:
+    def subsets(self, nums: list[int]) -> list[list[int]]:
+        res = []
+
+        def backtrack(i, path):
+            res.append(path[:])
+            for num_idx in range(i, len(nums)):
+                path.append(nums[num_idx])
+                backtrack(num_idx + 1, path)
+                path.pop()
+
+        backtrack(0, [])
+        return res
+```