The power of variability in the Vitaq AI Test Automation Tool is the secret sauce that makes a single Test Activity automatically generate tests for many user journeys combined with different sets of data. Vitaq’s allows test scripts in each Test Action to execute in a series of action sequences, to imitate our user journeys by effectively executing each action script to the next allowable action script in turn.
As QA testers we get to know our Test Space in great detail. When we are creating a Vitaq Test Activity, it is quite intuitive to draw out our required test action to next allowable action and then in each action we write our test scripts. Another great thing about Vitaq is that we can also make our test scripts data-driven, so we can generate our data into the test scripts each time Vitaq executes a test action script. Vitaq AI has the capability of choosing the next allowable action to go to and when it’s in that action It goes through the test script and for any data-driven requirement it auto-generates the test data and feeds that data into the test script and then we go on to next allowable action.
It is very easy to click through actions in the Test Activity to define your specific requirements for certain user journey’s. To make sure these are achieved during a Test Automation run, we specify targets on each sequence (User Journey). Then we leave the heavy lifting up to Vitaq AI which uses it’s AI Machine Learning Algorithms to choose which next allowable Test Actions to select and what test data to auto-generate by learning what its achieving in terms of QA Coverage and comparing this against the goals that you have defined.
Vitaq works with its AI going through the entire Test Activity choosing Action to next allowable Action. The user can control how much variability is deployed when choosing test actions and test data by settings in the preferences form.
When setting the Variability to high, Vitaq will use its variability algorithm to choose different Action to next allowable Action sequences and different test data values, rather than directly choosing only the action to action sequences and test data defined in the User Journey goals. The increased variability provides a users with the ability to ‘explore’ around the test space rather than just directly executing a limited number of ‘known about’ user-journeys.
Vitaq’s power of variability in each Test Activity Diagram is a great way to make sure your software under test is tested thoroughly and helps to ensure that you will pass the rigorous quality checks required in modern app development.
Let’s discuss how we can handle Variability in the Vitaq AI Test Automation Tool :-
1) Open the Test Activity Diagram on which you want to apply Variability.
2) Click on Edit on top menu bar and click on preferences.
3) Check on Use coverage checkbox plus Check on Use AI checkbox, There you go you would be able to see the Vitaq AI Variability and Variability Decay.
4) If Variability has been set to low by keeping slider to the left and Variability Decay is Kept high by keeping slider to the Right.
Then Vitaq will use a minimum amount of Variability and each run it starts will quickly reduce (decay) the amount of variability. What that means to the Test Automation is that Vitaq will use a precise and directed choice of next action to achieve the sequence and by that, you can achieve your sequence faster but you will lose the opportunity to explore around your test space by using Vitaq’s variability to auto-generate tests that you may not have thought of.
5) If Variability has been set to High by keeping slider to the Right and Variability Decay is Kept low by keeping slider to the Left.
Then Vitaq will bring into play a high level of Variability at the beginning of a Vitaq AI Test Automation run and that for each new seed run, Vitaq will gradually reduce (decay) that amount of variability. This setting might not achieve your user journey sequence targets as quickly but it does mean you will get choices that are valid because you have drawn your Test Activity a connected Test Actions to next allowable actions.
6) if Variability has been set to Medium by keeping slider in the Middle and Variability Decay is set to Medium by keeping slider to the Middle.
Then Vitaq will provide medium amount of variability (which is not too high and too low) but would be sufficient to go through rigorous user journey’s checks with some exploratory variability testing.
The Relationship to the amount of Variability and the rate at which Vitaq will decrease that Variability on each run (by setting the Variability Decay) is a key aspect for controlling Vitaq AI and making sure it keeps a focus on achieving the defined test goals for achieving user journeys.
Vitaq makes its choice of next test action by either deploying its Machine Learning AI Algorithm or its underlying Variability algorithm. By setting the Variability to high and the Variability Decay to low means the choice will be largely taken by the Variability Algorithms and on each run this will slowly switch over to the AI Machine learning choices driven by achieving the QA coverage goals defined in the targets.
By Setting the Variability to low then you are actually asking Vitaq AI Test Automation Tool to use its machine learning Algorithms much more than the variability Algorithms and the resulting Test Automation run will execute test scenarios that are directly following the defined user sequences.
One of the useful aspects of Vitaq is it will do things that test developers don’t think about and if you allow more variability you will get more tests that may create more conditions in your software under test that a test developer wouldn’t have thought about. That is what makes Vitaq a powerful bug finder.