View source for 20240037020. System and Method for Automated Software Testing simplified abstract (SMARTLYTICS LLC, DBA QUANTYZD)

=System and Method for Automated Software Testing=


==Organization Name==

[[:Category:SMARTLYTICS LLC, DBA QUANTYZD|SMARTLYTICS LLC, DBA QUANTYZD]]


[[Category:SMARTLYTICS LLC, DBA QUANTYZD]]

==Inventor(s)==

[[:Category:Syed Hamid of Redmond WA (US)|Syed Hamid of Redmond WA (US)]][[Category:Syed Hamid of Redmond WA (US)]]

==System and Method for Automated Software Testing - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240037020 titled 'System and Method for Automated Software Testing

==Simplified Explanation==

The abstract describes a system and method for automated software testing using machine learning algorithms. The system processes a mobile software application to identify screens, objects, and understand the operational flow. It then defines priorities, dependencies, and validation tests within the application. Based on this analysis, it automatically generates one or more testing scenarios for the application. These scenarios are executed on physical or virtual devices using an automated execution module.

* The system uses machine learning algorithms to automate software testing.
* It analyzes a mobile software application to identify screens and objects.
* It understands the operational flow of the application.
* It defines priorities and dependencies within the application.
* It defines validation tests for the application.
* It automatically generates testing scenarios based on the analysis.
* The testing scenarios are executed on physical or virtual devices.

Potential applications of this technology:

* Efficient and automated software testing for mobile applications.
* Improved accuracy and coverage of software testing.
* Time and cost savings in the software testing process.
* Scalability for testing multiple applications simultaneously.

Problems solved by this technology:

* Manual software testing is time-consuming and prone to errors.
* Identifying screens, objects, and dependencies within an application can be challenging.
* Generating comprehensive testing scenarios manually is a complex task.
* Testing on multiple devices can be resource-intensive.

Benefits of this technology:

* Increased efficiency and accuracy in software testing.
* Reduced time and cost associated with manual testing.
* Improved test coverage and reliability.
* Scalability for testing multiple applications and devices.
* Enhanced productivity of software testing teams.


==Original Abstract Submitted==

a system and method for automated software testing that uses machine learning algorithms to automatically generate and implement software testing based on an automated analysis of the software. in an embodiment, a mobile software application comprising one or more screens is processed through a trained machine learning algorithm to identify screens and objects, understand the operational flow of the application, define priorities and dependencies within the application, define validation tests, and automatically generate one or more testing scenarios for the application. the testing scenarios may then be fed to an automated execution module which installs the application on one or more physical or virtual devices and performs testing on the application installed on those devices according to the testing scenario.



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