Abstract: Mechanisms are provided to generate a test dataset for software application development. A baseline mixed reality (MR) environment simulation of an existing process is generated that models applications of an application landscape. A requirement for an application that is to be developed is received and a MR component model is generated to represent the application based on a machine learning computer model processing of the requirements data structure and a knowledge corpus. The MR component model modifies the baseline MR environment simulation, and executes the modified MR environment simulation to simulate the modified MR environment simulation. The simulation is monitored for user input specifying a contextual scenario and context data is collected from the MR component models of the modified MR environment simulation. A test dataset for testing a coded version of the SUD application is generated based on the contextual scenario and the collected data.

Abstract: Mechanisms are provided to generate a test dataset for software application development. A baseline mixed reality (MR) environment simulation of an existing process is generated that models applications of an application landscape. A requirement for an application that is to be developed is received and a MR component model is generated to represent the application based on a machine learning computer model processing of the requirements data structure and a knowledge corpus. The MR component model modifies the baseline MR environment simulation, and executes the modified MR environment simulation to simulate the modified MR environment simulation. The simulation is monitored for user input specifying a contextual scenario and context data is collected from the MR component models of the modified MR environment simulation. A test dataset for testing a coded version of the SUD application is generated based on the contextual scenario and the collected data.

Abstract: Aspects of this disclosure include a method for proactive cooling, a vehicle, and a computer program product for a proactive cooling system. One embodiment of the method may comprise creating a machine learning model of a physical object, and instrumenting the physical object with sensors to generate real-time data about the physical object and its operational environment. The method may further comprise generating, with the machine learning model, a predicted future temperature for the physical object using the real-time data about the physical object and its operational environment, and in response to the predicted future temperature exceeding a threshold temperature within a threshold time period, proactively cooling the physical object.