old_contents: import chatbot_brain
  import input_filters
  
  
  def test_initialize_bot():
      bot = chatbot_brain.Chatbot()
      assert len(bot.tri_lexicon) == 0
      assert len(bot.bi_lexicon) == 0
  
  
  def test_fill_lexicon():
      bot = chatbot_brain.Chatbot()
      bot.fill_lexicon()
      assert len(bot.tri_lexicon) > 0
      assert len(bot.bi_lexicon) > 0
  
  
  def test_compose_response():
      bot = chatbot_brain.Chatbot()
      output = bot.compose_response(input_sent="How are you doing?")
      assert "," not in output[0]
      for sentence in output:
          assert "." not in sentence[:-1]
  
new_contents: import chatbot_brain
  
  
  def test_initialize_bot():
      bot = chatbot_brain.Chatbot()
      assert len(bot.tri_lexicon) == 0
      assert len(bot.bi_lexicon) == 0
  
  
  def test_fill_lexicon():
      bot = chatbot_brain.Chatbot()
      bot.fill_lexicon()
      assert len(bot.tri_lexicon) > 0
      assert len(bot.bi_lexicon) > 0
  
  
  def test_compose_response():
      bot = chatbot_brain.Chatbot()
      output = bot.compose_response(input_sent="How are you doing?")
      assert "," not in output[0]
      for sentence in output:
          assert "." not in sentence[:-1]
  
  
  def test_i_filter_random_empty_words():
      u"""Assert the returned word is in the lexicon and is not a stop char."""
      bot = chatbot_brain.Chatbot()
      words = [""]
      assert bot.i_filter_random(words) == u"What a funny thing to say!"
  
  # untested methods:
  # i_filter_random
  # o_filter_random
  # _create_chains
  # _pair_seed
  # _chain_filters
  # _filter_recursive
  
subject: Add test_i_filter_random_empty_words() to assert that a list that contains an empty string will return the stock phrase