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Artificial Intelligence in Automation

Artificial Intelligence and software automation testing have never really been discussed together as being a possible solution.  AI starts playing an important role in testing and it has already begun transforming it as a function in helping development teams to catch bugs earlier, assessing and correcting scripts faster than ever before.

BOA is a pioneering delivered solution that will have the ability to self-learn and test applications without much human intervention beyond the implementation stage, making it genuinely autonomous and intelligent.

Interpolating Machine Learning into Cloudpipe’s framework, aiding the recognition of patterns when building object model based repositories (POM & DOM) to optimize outputs, and move on from yesterday’s laborious methods to tomorrow’s development and testing.

BOA will help our clients improve agility and predictability while optimizing efforts in testing by integrating AI techniques to test automation. Additionally, BOA as a solution is a Machine learning project for designing and executing a runtime model.

The library is continuously evolving to pre-recognise patterns by building class structures.

The BOA Process Flow


Web Harvester

Data Representation

Precision Check


Feature Engineering

Predicted Labels

AI Model

​​Combining the best advantages of AI within QA test automation, BOA has a simple strategy described in these three targets.

Eliminate test coverage overlaps


Mapping the whole application under test and storing the data for further analysis;

Running BOA algorithms we compare and detect changes in applications;

Developing an action script updating test automation framework.


Optimize efforts with predictable testing

BOA groups elements into classes by identifying similarities among them;


Improve performance on specific tasks with data by understanding and running multiple testing scenarios;

It is also able to predict in which “class grouping” a new element is going to be clustered.


Move to defect prevention instead of defect detection


Cloudpipe's Total Quality Management process works on prevention by detecting test automation issues after root cause defects identification and directing to the exact location where they must be corrected;


Our team combines the best advantages of AI within QA test automation leading to an integrated end result.

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