1. A method for optimizing testing of software production incidents, the method comprising: categorizing, via a processor, an incident ticket received from one or more sources based on one or more pre-defined parameters, the incident ticket corresponding to an obstruction in a software production; in response to categorization, analyzing, via the processor, the incident ticket using a machine learning algorithm to identify one or more keywords in the incident ticket; identifying, via the processor, a location of the incident ticket based on the one or more keywords, a test workspace corresponding to the incident ticket based on the location, and a plurality of specific test cases corresponding to the incident ticket based on the test workspace, the identification leading to a first scenario and a second scenario; in the first scenario, initiating, via the processor, a learning process based on intelligence gathered from a manual processing of the incident ticket; and in the second scenario, identifying, via the processor, a test environment for the plurality of specific test cases; and executing, via the processor, the plurality of specific test cases in the test environment, wherein the first scenario corresponds to a negative identification of at least one of the location, the test workspace, and the plurality of specific test cases, wherein the second scenario corresponds to a positive identification of the location, the test workspace, and the plurality of specific test cases, wherein the incident ticket resulting in the first scenario comprises a new incident ticket unrelated to a plurality of past incident tickets and not having at least one of a corresponding location, a corresponding test workspace, and a corresponding specific test case, and wherein the manual processing of the new incident ticket comprises generating at least one of a solution, a location, a test workspace, a test case, and a test environment.