Delta Code Identification and Validation Using Artificial Intelligence

A method comprising:

• at a computing platform comprising at least one processor, a communication interface, and memory:
• using an artificial intelligence (AI) engine to convert historical information into machine readable information, wherein the historical information comprises one or more peer review comments and one or more historical defects;
• configuring a Q learning module using the machine readable information and a database of scenarios, wherein the configuring prepares the Q learning module to receive delta code and identify one or more scenarios from the database of scenarios associated with the delta code;
• receiving first delta code from an enterprise user device;
• inputting the first delta code into the Q learning module;
• outputting, using the Q learning module, based on the first delta code, and based on the machine readable information and the database of scenarios, one or more scenarios associated with the first delta code;
• outputting, based on the one or more scenarios and using an association mapping module, one or more unit test cases, wherein the one or more unit test cases are used to validate the first delta code;
• validating the first delta code using the one or more unit test cases;
• and
• sending, to an enterprise system, the validated first delta code and commands directing the enterprise system to deploy the validated first delta code, wherein the validated first delta code and the commands cause the enterprise system to deploy the validated first delta code.

One or more non-transitory computer-readable storing instructions that, when executed by a computing platform comprising at least one processor, a communication interface, and memory, cause the computing platform to:

• use an artificial intelligence (AI) engine to convert historical information into machine readable information, wherein the historical information comprises one or more peer review comments and one or more historical defects;
• configure a Q learning module using the machine readable information and a database of scenarios, wherein the configuring prepares the Q learning module to receive delta code and identify one or more scenarios from the database of scenarios associated with the delta code;
• receive first delta code from an enterprise user device;
• input the first delta code into the Q learning module;
• output, using the Q learning module, based on the first delta code, and based on the machine readable information and the database of scenarios, one or more scenarios associated with the first delta code;
• output, based on the one or more scenarios and using an association mapping module, one or more unit test cases, wherein the one or more unit test cases are used to validate the first delta code;
• validate the first delta code using the one or more unit test cases;
• and
• send, to an enterprise system, the validated first delta code and commands directing the enterprise system to deploy the validated first delta code, wherein the validated first delta code and the commands cause the enterprise system to deploy the validated first delta code.