Abstract: Computer-implemented methods, computer program products, and computer systems for testing a voice assistant device may include one or more processors configured for receiving test data from a database, wherein the test data may include a first set of coding parameters and a first user utterance having an expected device response. Further, the one or more processors may be configured for generating a first modified user utterance by applying the first set of coding parameters to the first user utterance, wherein the first modified user utterance is acoustically different than the first user utterance. The one or more processors may be configured for audibly presenting the first modified user utterance to a voice assistant device, receiving a first device response from the voice assistant device, and determining whether the first voice assistant response is substantially similar to the expected device response.

Abstract: A computer-implemented method for sender activated mobile call overloading (SAMCO) is described that includes processors configured for receiving request call data comprising a data request initiated by a sending mobile device intended for a receiving mobile device, receiving active call data corresponding to a telephone call placed by the sending mobile device to the receiving mobile device, wherein the active call data comprises the data request, determining that the receiving mobile device is subscribed to a data request service configured to execute the data request, determining that the sending mobile device is authorized to access the receiving mobile device, and responsive to determining that the sending mobile device is authorized, the method includes processors configured for transmitting the data request to the receiving mobile device.

Abstract: A computer implemented method manages zero-day vulnerabilities in an application package having a set of components. The computer ingests data about potential vulnerabilities from a plurality of data sources. Using a set of machine learning models, the computer predicts a vulnerability based on of the data that was ingested. The computer performs a code analysis of the set of components to identify a possibility of the vulnerability impacting the application package. The computer generates a recommendation to resolve the vulnerability based on the code analysis and the data that was ingested. The computer manages the recommendation in a private blockchain.

Abstract: A system, method, and computer program product for implementing microservice deployment is provided. The method includes receiving definitions associated with microservices related to implementing hardware and software solutions with respect to hardware and software systems. In response, a definition file and associated code comprising the definitions and associated dependencies associated with the microservices are generated. The microservices are deployed to a container orchestration system cluster on a cloud structure and a service mesh and machine learning module are installed within the container orchestration system cluster. Proxies comprising a proxy for each pair of dependencies are generated and network traffic passing through each proxy is monitored. A malfunction of a hardware or software system is detected and an associated network route passing through an associated proxy is disabled.

Abstract: Embodiments of the present invention provide a computer system a computer program product, and a method that comprises converting the retrieved data to a uniform syntax for data assessment; performing a query on a plurality of external data sources for additional information associated with the converted data; analyzing a plurality of indicative markers associated with the retrieved data and the additional information; generating a plurality of machine learning models associated with the converted data based on the analysis of each indicative markers within the plurality of indicative markers; dynamically selecting at least one generated machine learning model within the plurality of generated machine learning models associated with the retrieved data based on an analysis of the plurality of indicative markers associated with the retrieved data and the additional information; and automatically verifying an accuracy value associated with the at least one selected generated machine learning model.

Abstract: Computer-implemented methods, computer program products, and computer systems for testing a voice assistant device may include one or more processors configured for receiving test data from a database, wherein the test data may include a first set of coding parameters and a first user utterance having an expected device response. Further, the one or more processors may be configured for generating a first modified user utterance by applying the first set of coding parameters to the first user utterance, wherein the first modified user utterance is acoustically different than the first user utterance. The one or more processors may be configured for audibly presenting the first modified user utterance to a voice assistant device, receiving a first device response from the voice assistant device, and determining whether the first voice assistant response is substantially similar to the expected device response.