Unit test coverage

As a Test Engineer, you should validate the unit tests coverage. Many times, we don't have access to all source code, and  it could be enough to check metrics in a tool like Sonar.
Otherwise, you could read unit tests and determine if programmers are covering the most important cases and suggest new scenarios.

In order to do it, I propose these validations:

Size:
For collections:

• Test with an empty collection
• A collection with 1 item
• The smallest interesting case 
• A collection with several items

Dichotomies:

• Vowels / Non-vowels
• Even / Odd 
• Positive / Negative
• Empty / Full.

Boundaries:

• If the function behaves differently for values near a particular threshold.

Order:

• If the function behaves differently when the values are in different orders. Identify each of those orders.

Example in Python:

import unittest

class TestStockPriceSummary(unittest.TestCase):
    """ Test class for function a1.stock_price_summary. """
 
 def test_empty_list(self):
  """ 
  Return an empty tuple when price_changes is empty.
  """
  price_changes = []
  actual = a1.stock_price_summary(price_changes)
  expected = (0,0)
  self.assertEqual(actual,expected)
 
 def test_single_item_positive(self):
  '''
  Test when the list only includes a positive item
  '''
  price_changes = [2.45]
  actual = a1.stock_price_summary(price_changes)
  expected = (2.45,0)
  self.assertEqual(actual,expected)
 
 def test_single_item_negative(self):
  '''
  Test when the list only includes a negative item
  '''
  price_changes = [-2.45]
  actual = a1.stock_price_summary(price_changes)
  expected = (0,-2.45)
  self.assertEqual(actual,expected)
 
 def test_single_item_zero(self):
  '''
  Test when the list contains only an item = 0
  '''
  price_changes = [0]
  actual = a1.stock_price_summary(price_changes)
  expected = (0,0)
  self.assertEqual(actual,expected)
 
 def test_general_case(self):
  """ 
  Return a 2-item tuple where the first item is the sum of the gains in price_changes and
  the second is the sum of the losses in price_changes.
  """
  price_changes = [0.01, 0.03, -0.02, -0.14, 0, 0, 0.10, -0.01]
  actual = a1.stock_price_summary(price_changes)
  expected = (0.14, -0.17)
  self.assertEqual(actual,expected)
 
if __name__ == '__main__':
    unittest.main(exit=False)