Test Data Clarity

Permutation techniques may make data easier to grasp by making the datasets small and commonly used, but we can make our data clearer still by describing each row in its own free text fields, allowing testers to make a simple comparison between the free text (which is generally displayed on output), and actions based on fields which tend not to be directly displayed. Use of free text fields with some correspondence to the internals of the record allows output to be checked more easily.


Testers often talk about items of data, referring to them by anthropomorphic personification - that is to say, they give them names. This allows shorthand, but also acts as jargon, excluding those who are not in the know. Setting this data, early on in testing, to have some meaningful value can be very useful, allowing testers to sense check input and output data, and choose appropriate input data for investigative tests.


Reports, data extracts and sanity checks can also make use of these; sorting or selecting on a free text field that should have some correspondence with a functional field can help spot problems or eliminate unaffected data. Data is often used to communicate and illustrate problems to coders and to the business. However, there is generally no mandate for outside groups to understand the format or requirements of test data. Giving some meaning to the data that can be referred to directly can help with improving mutual understanding.

Clarity helps because:
· Improves communication within and outside the team

· Reduces test errors caused by using the wrong data

· Allows another method way of doing sanity checks for corrupted or inconsistent data

· Helps when checking data after input

· Helps in selecting data for investigative tests