Abstract: Storing a set of emulated devices, the set of emulated devices including a plurality of different emulated devices. Obtaining one or more filter parameters. Selecting, based on the filter parameters, a subset of emulated devices from the set of emulated devices. Initiating testing of an application on a particular emulated device of the subset of emulated devices. Obtaining, at run-time while the application is being tested, first error log data from the testing of the application on the particular emulated device of the subset of emulated devices. Parsing, at run-time while the application is being tested, the first error log data, thereby generating a set of first error log data components. Adjusting, at run-time while the application is being tested, one or more weights of a machine learning model based on the set of first error log data components. Providing, at run-time while the application is being tested, the set of first error log data components to the machine learning model.

Abstract: Storing a set of emulated devices, the set of emulated devices including a plurality of different emulated devices. Obtaining one or more filter parameters. Selecting, based on the filter parameters, a subset of emulated devices from the set of emulated devices. Initiating testing of an application on a particular emulated device of the subset of emulated devices. Obtaining, at run-time while the application is being tested, first error log data from the testing of the application on the particular emulated device of the subset of emulated devices. Parsing, at run-time while the application is being tested, the first error log data, thereby generating a set of first error log data components. Adjusting, at run-time while the application is being tested, one or more weights of a machine learning model based on the set of first error log data components. Providing, at run-time while the application is being tested, the set of first error log data components to the machine learning model.

Abstract: Obtaining a configuration hook. Obtaining a base configuration of a remote system using the configuration hook. Obtaining a system-specific model associated with the configuration hook and the remote system. Obtaining one or more pre-built test accelerators. Obtaining a deep machine learning model. Generating, based on the base configuration, the system-specific model, the one or more pre-built test accelerators and the deep machine learning model, a custom configuration model. Generating a plurality of user journeys to be autonomously tested. Generating, based on the custom configuration model and the plurality of user journeys to be autonomously tested, a plurality of autonomous test scripts. Autonomously pre-configuring at run-time the plurality of autonomous test scripts. Autonomously executing the plurality of autonomous test scripts. Generating, based on the autonomously executed plurality of autonomous test scripts, one or more autonomous test reports.

Abstract: Obtaining a configuration hook. Obtaining a base configuration of a remote system using the configuration hook. Obtaining a system-specific model associated with the configuration hook and the remote system. Obtaining one or more pre-built test accelerators. Obtaining a deep machine learning model. Generating, based on the base configuration, the system-specific model, the one or more pre-built test accelerators and the deep machine learning model, a custom configuration model. Generating a plurality of user journeys to be autonomously tested. Generating, based on the custom configuration model and the plurality of user journeys to be autonomously tested, a plurality of autonomous test scripts. Autonomously pre-configuring at run-time the plurality of autonomous test scripts. Autonomously executing the plurality of autonomous test scripts. Generating, based on the autonomously executed plurality of autonomous test scripts, one or more autonomous test reports.

Abstract: Obtaining a configuration hook. Obtaining a base configuration of a remote system using the configuration hook. Obtaining a system-specific model associated with the configuration hook and the remote system. Obtaining one or more pre-built test accelerators. Obtaining a deep machine learning model. Generating, based on the base configuration, the system-specific model, the one or more pre-built test accelerators and the deep machine learning model, a custom configuration model. Generating a plurality of user journeys to be autonomously tested. Generating, based on the custom configuration model and the plurality of user journeys to be autonomously tested, a plurality of autonomous test scripts. Autonomously pre-configuring at run-time the plurality of autonomous test scripts. Autonomously executing the plurality of autonomous test scripts. Generating, based on the autonomously executed plurality of autonomous test scripts, one or more autonomous test reports.