Natural language analysis of a command line using a machine learning model to generate a natural language description of the command line

In one or more embodiments, a command is repeatedly input a predetermined number of times into a machine learning model to generate a plurality of different natural language (NL) descriptions. The plurality of different NL descriptions are input into the machine learning model to generate a plurality of different check commands. A plurality of similarity metrics are determined by comparing each check command from the plurality of different check commands to the command. A check command from the plurality of different check commands that is most similar to the command is identified based on the plurality of similarity metric. Based on such, a NL description from the plurality of different NL descriptions is caused to be displayed, this being the NL description previously input into the machine learning model to generate said check command. The machine learning model may be that of a deep learning autoregressive language model. The method may also output a quality metric associated with the NL description wherein the quality metric is determined based on a distance value form a plurality of distance values associated with the check command.