Monkey test
In computer science, a Monkey test (aka. Mark Testing) is an automated test that runs with no specific test in mind. The monkey in this case is the producer of any input. For example, a monkey test can enter random strings into text boxes to ensure handling of all possible user input or provide garbage files to check for loading routines that have blind faith in their data. The test monkey is technically known to conduct random testing, which is in the category of black-box testing.
The name 'monkey' comes from the adage that ‘ thousand monkeys at a thousand typewriters will eventually type out the entire works of Shakespeare’. Cf. the Infinite monkey theorem.
Types of monkey test
Monkey Button Push Testing
This is a term for when there is a written testing procedure that needs repetitive execution without thought from the user. Similar to the monkey learning to push the red button in order to get the banana, this test only requires the ability to read a step by step procedure, and hit the keys and verify the correctness of the result.
Smart Monkey Testing
Input are generated from probability distributions that reflect actual expected usage statistics—e.g., from user profiles. There are different levels of IQ in smart monkey testing. In the simplest, each input is considered independent of the other inputs. That is, a given test requires an input vector with five components. In low IQ testing, these would be generated independently. In high IQ monkey testing, the correlation (e.g., the covariance) between these input distribution is taken into account. In all branches of smart monkey testing, the input is considered as a single event.[1]
Brilliant Monkey Testing
The inputs are created from a random regular expression or random finite-state machine model of user behavior. That is, not only are the values determined by probability distributions, but the sequence of values and the sequence of states in which the input provider goes is driven by specified probabilities.[1]
Dumb Monkey Testing
Inputs are generated from a uniform probability distribution without regard to the actual usage statistics.[1]