Abstract: Disclosed are techniques for training and utilizing a machine learning model for automatically accelerating technical incident triage. A historical dataset is combined from a plurality of sources corresponding to historical technical incidences and how they were resolved, including what persons or responders were involved in responding to the incident. This historical dataset is processed for input into a machine learning model which is trained to output a ranking of historical incidences based on similarity to an input incident. Machine logic then automatically selects a responder for the incident based on which available responders previously resolved the ranked historical incidences, selecting responders from the most similar historical incidences if they are available, and communicating information from the ranked historical incidences to assist in diagnosing and resolving the input incident.

Abstract: A method, system, and computer program product for implementing automated software application generation is provided. The method includes scanning source code for identifying missing elements of hardware and software parameters associated with functional operation of software for development. The hardware and software parameters are analyzed and converted into configurable digital bins. An automation parameter is generated. The automation parameter is associated with portions of the software configured for automatic development and generation. Corrective actions associated with automating development of the software are generated based on the automation parameter and it is determined that the automation parameter is within a specified range of the portions. The corrective actions are executed with respect to development of the software and the software is generated.

Abstract: A method, system, and computer program product for implementing automated software application generation is provided. The method includes scanning source code for identifying missing elements of hardware and software parameters associated with functional operation of software for development. The hardware and software parameters are analyzed and converted into configurable digital bins. An automation parameter is generated. The automation parameter is associated with portions of the software configured for automatic development and generation. Corrective actions associated with automating development of the software are generated based on the automation parameter and it is determined that the automation parameter is within a specified range of the portions. The corrective actions are executed with respect to development of the software and the software is generated.