Connascence of Algorithm

Connascence of algorithm is when multiple components must agree on a particular algorithm.

In Data Transmission

Connascence of algorithm frequently occurs when two entities must manipulate data in the same way. For example, if data is being transmitted from one service to another, some sort of checksum algorithm is commonly used. The sender and receiver must agree on which algorithm is to be used. If the sender changes the algorithm used, the receiver must change as well.

In Data Validation and Encoding

Consider a hypothetical piece of software that required users to provide a valid email address when creating an account. The software must validate that the email address is valid, but this might happen in several places, including:

  • In a database model object.
  • In a webapp 'controller' class method.
  • In a form field in the front-end UI.

These pieces of code might well be in different languages, and will almost certainly be far apart from each other. The consequence of these algorithms being different might include users not being able to register, but recieving no feedback as to why.

Another common example of connascence of algorithm is when unicode strings are written to disk. Imagine a hypothetical piece of software that writes a data string to a cache file on disk:

def write_data_to_cache(data_string):
    with open('/path/to/cache', 'wb') as cache_file:

A matching function is used to retrieve the data from the cache file:

def read_data_from_cache():
    with open('/path/to/cache', 'rb') as cache_file:

The connascence of algorithm here is that both functions must agree on the encoding being used. If the write_data_to_cache function changes to encrypt the data on disk (the data being stored is potentially sensitive), the read_data_from_cache must also be updated.

In Test Code

Test code often contains connascence of algorithm. Consider this hypothetical test:

def test_user_fingerprint(self):
    user ="Thomi Richards")
    actual = user.fingerprint()
    expected = hashlib.md5(
    self.assertEqual(expected, actual)

This test is supposed to be testing that the 'fingerprint' method of the User class works as expected. However, it contains connascence of algorithm, which limits it's effectiveness. If the User class ever changes the way fingerprints are calculated, this test will fail.