18092519. NATURAL LANGUAGE PROCESSING ENGINE FOR AUTOMATED DETECTION OF SOURCE CODE DISCREPANCIES simplified abstract (BANK OF AMERICA CORPORATION)

NATURAL LANGUAGE PROCESSING ENGINE FOR AUTOMATED DETECTION OF SOURCE CODE DISCREPANCIES

Organization Name

BANK OF AMERICA CORPORATION

Inventor(s)

Marcus Raphael Matos of Richardson TX (US)

Jack Lawson Bishop, Iii of Evanston IL (US)

Robert Cain Durbin, Jr. of New Hope PA (US)

Daniel Joseph Serna of The Colony TX (US)

Benjamin Tweel of Romeoville IL (US)

Jake Michael Yara of Mint Hill NC (US)

NATURAL LANGUAGE PROCESSING ENGINE FOR AUTOMATED DETECTION OF SOURCE CODE DISCREPANCIES - A simplified explanation of the abstract

This abstract first appeared for US patent application 18092519 titled 'NATURAL LANGUAGE PROCESSING ENGINE FOR AUTOMATED DETECTION OF SOURCE CODE DISCREPANCIES

The abstract describes a system for automated detection of source code discrepancies using machine learning and natural language processing engines.

• The system receives a data transmission with a text file and a source code file.
• It processes the source code file with a machine learning engine to identify updates.
• It processes the text file with a natural language processing engine to identify expected updates.
• The system then compares the identified updates with the expected updates to identify differences.
• Finally, the system performs a remedial action to address the identified differences.

Potential Applications: - Software development and quality assurance - Code review and version control - Automated bug detection and resolution

Problems Solved: - Streamlining the process of identifying and resolving source code discrepancies - Improving code quality and reducing errors in software development

Benefits: - Increased efficiency in detecting and resolving code discrepancies - Enhanced accuracy in identifying updates and expected changes - Improved overall quality of software development projects

Commercial Applications: Automated source code analysis tools for software development companies to improve code quality and streamline development processes.

Questions about the technology: 1. How does the system utilize machine learning to identify updates in the source code? 2. What are the key advantages of using natural language processing in detecting expected updates in the text file?

Original Abstract Submitted

Systems, computer program products, and methods are described herein for automated detection of source code discrepancies. The present disclosure is configured to receive a data transmission including a text file and a source code file; process the source code file via a machine learning engine, where an output of the machine learning engine includes a plurality of identified updates; process the text file via a natural language processing engine, where an output of the natural language processing engine includes a plurality of expected updates; identify a difference between the plurality of identified updates and the plurality of expected updates; and perform a remedial action.