input: Write a function to evaluate and compare the performance of two different heuristics algorithms by measuring the time taken by each algorithm to process the given inputs. Return a message indicating which algorithm is faster or if they have the same performance time. If both input data sets are provided, ensure that the function runs both algorithms with their respective inputs and measures the time for each run.
  assert evaluate_algorithms(['data1', 'data2'])==None
  assert evaluate_algorithms(['data3', 'data4'])==None
  assert evaluate_algorithms(['data5', 'data5'])==None
  assert evaluate_algorithms([])==None
  assert evaluate_algorithms(['data6'])==None
output: def evaluate_algorithms(inputs):
      if len(inputs) != 2:
          return None
      import time
      def heuristic_algorithm(data):
          time.sleep(0.1)  # Simulate processing time
      start_time_1 = time.time()
      heuristic_algorithm(inputs[0])
      time_taken_1 = time.time() - start_time_1
      start_time_2 = time.time()
      heuristic_algorithm(inputs[1])
      time_taken_2 = time.time() - start_time_2
      if time_taken_1 < time_taken_2:
          return "First algorithm is faster."
      elif time_taken_1 > time_taken_2:
          return "Second algorithm is faster."
      else:
          return "Both algorithms have the same performance time."