Update merge_server.py

merge_server.py

@@ -219,7 +219,14 @@ def predict():
                 "recommended_name": "Binary Search (O(log n))",
                 "recommended_code": "import bisect\ndef [FUNC_NAME]_binary([ARGS]):\n    idx = bisect.bisect_left([FIRST_ARG], target)\n    if idx < len([FIRST_ARG]) and [FIRST_ARG][idx] == target:\n        return idx\n    return -1"
             },
-
+            "Nested Iterative": {
+                "space": "O(1)",
+                "explanation": "⚠️ WARNING: Nested loops usually indicate a 'brute force' O(n^2) time complexity. This scales poorly for large datasets and can often be optimized.",
+                "improvements": ["Check if the inner loop can be replaced with a Hash Map (dictionary) for O(1) lookups.", "If analyzing contiguous subarrays, switch to the Sliding Window technique (O(n))."],
+                "optimized_code": "def [FUNC_NAME]([ARGS]):\n    n = len([FIRST_ARG])\n    # If you MUST use nested loops, ensure the inner loop shrinks each pass (j = i + 1)\n    for i in range(n):\n        for j in range(i + 1, n):\n            pass # Your logic here\n    return [FIRST_ARG]",
+                "recommended_name": "Hash Map Lookup OR Sliding Window (O(n))",
+                "recommended_code": "# --- OPTION 1: HASH MAP (For finding pairs/duplicates) ---\ndef [FUNC_NAME]_hashmap([ARGS]):\n    seen = set()\n    for item in [FIRST_ARG]:\n        if item in seen: return item\n        seen.add(item)\n    return [FIRST_ARG]\n\n# --- OPTION 2: SLIDING WINDOW (For subarrays) ---\ndef [FUNC_NAME]_window([ARGS], k=2):\n    # Assumes [FIRST_ARG] is a list of numbers\n    window_sum = sum([FIRST_ARG][:k])\n    for i in range(len([FIRST_ARG]) - k):\n        window_sum = window_sum - [FIRST_ARG][i] + [FIRST_ARG][i+k]\n    return window_sum"
+            },
             # --- RECURSION, DP, & MATH ---
             "Fibonacci Sequence": {
                 "space": "O(n)",