Abstract: A system includes a memory and a processor coupled to the memory. The processor renders a virtual environment on a user device. The processor detects that a first view of the virtual environment has been rendered and accesses from the memory a first expected view pattern that corresponds to the first view. The processor compares the first view to the first expected view pattern and detects that a pattern of one or more visual elements in the first view does not match with an expected pattern of visual elements in the first expected view pattern. In response, the processor determines that an error has occurred relating to rendering the virtual environment. The processor obtains a solution corresponding to the error and applies the solution to resolve the detected error.

Abstract: Aspects of the disclosure relate to conducting automated web service testing in a continuous integration and delivery test deployment environment using artificial intelligence (AI) generated test data. In some embodiments, a computing platform may receive, from a developer computing platform, a test code request, receive, from a web service computing platform, a training data set, configure a test data set based on the training data set and the test code request, use AI engine to apply one or more corrections to the test data set based on the test code request and to produce a corrected test data set, execute the test code using the corrected test data set to produce test code output results, and send, to the developer computing platform, the test code output results.

Abstract: Aspects of the disclosure relate to conducting automated web service testing in a continuous integration and delivery test deployment environment using artificial intelligence (AI) generated test data. In some embodiments, a computing platform may receive, from a developer computing platform, a test code request, receive, from a web service computing platform, a training data set, configure a test data set based on the training data set and the test code request, use AI engine to apply one or more corrections to the test data set based on the test code request and to produce a corrected test data set, execute the test code using the corrected test data set to produce test code output results, and send, to the developer computing platform, the test code output results.

Abstract: A system includes a memory and a processor coupled to the memory. The processor runs a software application on a simulated user device to render a virtual environment on the simulated user device. The processor detects that a first view of the virtual environment has been rendered and accesses from the memory a first expected view pattern that corresponds to the first view. The processor compares the first view to the first expected view pattern and detects that a pattern of one or more visual elements in the first view does not match with an expected pattern of visual elements in the first expected view pattern. In response, the processor determines that an error has occurred relating to rendering the virtual environment by the software application. The processor obtains a solution corresponding to the error and applies the solution to the software application to resolve the detected error.

Abstract: A system includes a memory and a processor coupled to the memory. The processor runs a software application on a simulated user device to render a virtual environment on the simulated user device. The processor detects that a first view of the virtual environment has been rendered and accesses from the memory a first expected view pattern that corresponds to the first view. The processor compares the first view to the first expected view pattern and detects that a pattern of one or more visual elements in the first view does not match with an expected pattern of visual elements in the first expected view pattern. In response, the processor determines that an error has occurred relating to rendering the virtual environment by the software application. The processor obtains a solution corresponding to the error and applies the solution to the software application to resolve the detected error.

Abstract: A system includes a memory and a processor coupled to the memory. The processor runs a software application on a simulated user device to render a virtual environment on the simulated user device. In response to detecting an error associated with generation of the virtual environment by the software application, the processor searches a list of solutions based on the detected error, wherein each solution in the list corresponds to a known error associated with generation of the virtual environment on the real-world user device. The processor obtains a solution corresponding to the detected error from the list, wherein the solution comprises a revised source code or instructions to revise a source code of the software application to resolve the respective error. The processor determines and revises a portion of the source code of the software application relating to the error based on the revised source code in the solution.

Abstract: A system includes a memory and a processor coupled to the memory. The processor runs a software application on a simulated user device to render a virtual environment on the simulated user device. In response to detecting that the software application has rendered a video clip in the virtual environment, the processor converts the video clip into metadata. The processor compares a first metadata associated with a first frame of the video clip with a second metadata associated with at least one second frame of the video clip before or after the first frame. In response to determining that the first frame and the second frame do not conform to a pre-configured transition, the processor determines that an error has occurred in relation to rendering the video clip. The processor obtains a solution corresponding to the error and applies the solution to the software application to resolve the detected error.

Abstract: A system for generating non-fungible token-based test suites from design diagrams comprises a processor associated with a server. The processor is configured to obtain image objects representing a workflow associated with a design diagram and a user profile of a user. The processor is configured to generate a design non-fungible token (NFT) associated with the design diagram to verify a design diagram ownership. The processor is configured to convert the image objects of the design diagram into corresponding text objects and to process the corresponding text objects of the design diagram to generate a plurality of text datasets corresponding to the workflow of the design diagram, analyze the plurality of the text datasets and generate a test suite which comprises a set of test scripts corresponding to the design diagram, and generate a test case NFT associated with the test suite to verify a test suite ownership.

Abstract: Aspects of the disclosure relate to conducting automated web service testing in a continuous integration and delivery test deployment environment using artificial intelligence (AI) generated test data. In some embodiments, a computing platform may receive, from a developer computing platform, a test code request, receive, from a web service computing platform, a training data set, configure a test data set based on the training data set and the test code request, use AI engine to apply one or more corrections to the test data set based on the test code request and to produce a corrected test data set, execute the test code using the corrected test data set to produce test code output results, and send, to the developer computing platform, the test code output results.

Abstract: Aspects of the disclosure relate to conducting automated web service testing in a continuous integration and delivery test deployment environment using artificial intelligence (AI) generated test data. In some embodiments, a computing platform may receive, from a developer computing platform, a test code request, receive, from a web service computing platform, a training data set, configure a test data set based on the training data set and the test code request, use AI engine to apply one or more corrections to the test data set based on the test code request and to produce a corrected test data set, execute the test code using the corrected test data set to produce test code output results, and send, to the developer computing platform, the test code output results.

Abstract: Aspects of the disclosure relate to conducting automated web service testing in a continuous integration and delivery test deployment environment using artificial intelligence (AI) generated test data. In some embodiments, a computing platform may receive, from a developer computing platform, a test code request, receive, from a web service computing platform, a training data set, configure a test data set based on the training data set and the test code request, use AI engine to apply one or more corrections to the test data set based on the test code request and to produce a corrected test data set, execute the test code using the corrected test data set to produce test code output results, and send, to the developer computing platform, the test code output results.

Abstract: Aspects of the disclosure relate to conducting automated web service testing in a continuous integration and delivery test deployment environment using artificial intelligence (AI) generated test data. In some embodiments, a computing platform may receive, from a developer computing platform, a test code request, receive, from a web service computing platform, a training data set, configure a test data set based on the training data set and the test code request, use AI engine to apply one or more corrections to the test data set based on the test code request and to produce a corrected test data set, execute the test code using the corrected test data set to produce test code output results, and send, to the developer computing platform, the test code output results.