{
  "task_id": "hard-1",
  "difficulty": "hard",
  "description": "Optimize the function to find the maximum sum contiguous subarray (Kadane's algorithm). Current O(N^3) approach is too slow.",
  "buggy_code": "def max_subarray_sum(arr):\n    if not arr: return 0\n    max_sum = float('-inf')\n    n = len(arr)\n    for i in range(n):\n        for j in range(i, n):\n            current_sum = 0\n            for k in range(i, j + 1):\n                current_sum += arr[k]\n            if current_sum > max_sum:\n                max_sum = current_sum\n    return max_sum",
  "test_code": "\nimport unittest\nimport random\nclass TestHard(unittest.TestCase):\n    def test_basic(self):\n        self.assertEqual(max_subarray_sum([-2,1,-3,4,-1,2,1,-5,4]), 6)\n    def test_all_negative(self):\n        self.assertEqual(max_subarray_sum([-5, -2, -9]), -2)\n    def test_empty(self):\n        self.assertEqual(max_subarray_sum([]), 0)\n    def test_large(self):\n        random.seed(42)\n        arr = [random.randint(-100, 100) for _ in range(300)]\n        ans = max_subarray_sum(arr)\n        self.assertIsInstance(ans, int)\n",
  "optimal_time_seconds": 0.1
}