MUMBAI, India, July 13 -- Intellectual Property India has published a patent application (202641082727 A) filed by Dr. Bechoo Lal; Ramakrishna Kosuri; Dr. Murthy Ravaleedhar Reddy; Dr. S. Ranjana; Dr. M. Padmaja; Usman K; Sharada Polusani; Dr. R. Monisha; Dr. Rohit Kumar Verma; Ms. Tanvi; Dr. Aashdeep Singh; and Sakshi Dhawan on July 05, 2026, for An Artificial Intelligence–driven Software Development System For Automated Code Generation, Testing, And Optimization.
Inventors include Dr. Bechoo Lal; Ramakrishna Kosuri; Dr. Murthy Ravaleedhar Reddy; Dr. S. Ranjana; Dr. M. Padmaja; Usman K; Sharada Polusani; Dr. R. Monisha; Dr. Rohit Kumar Verma; Ms. Tanvi; Dr. Aashdeep Singh; and Sakshi Dhawan.
The application for the patent was published on July 10, 2026, under issue no. 28/2026.
Abstract: The present invention relates to an Artificial Intelligence–Driven Software Development System for Automated Code Generation, Testing, and Optimization. The system is designed to automate and improve major stages of the software development lifecycle by converting user requirements into reliable, testable, and optimized software code. The invention receives input in the form of natural language instructions, structured specifications, user stories, workflow descriptions, database requirements, or application programming interface requirements. A requirement interpretation module analyzes the input and identifies software functions, input parameters, output conditions, data flow, execution logic, and system constraints. Based on the interpreted requirement, an artificial intelligence code generation engine generates source code, software modules, functions, classes, database models, user interface components, API endpoints, configuration files, and deployment scripts. The generated code is checked by a validation module for syntax correctness, dependency availability, compatibility, data type consistency, and coding standards. An automated testing module generates and executes suitable test cases to verify functional correctness, boundary conditions, exception handling, regression behavior, and security aspects. If defects are detected, a bug detection and correction module identifies logical errors, runtime issues, vulnerabilities, and failed test conditions and provides automatic or assisted correction. The system further includes an optimization engine that improves execution speed, memory usage, scalability, maintainability, database performance, and resource efficiency. A documentation module generates comments, API descriptions, test reports, correction summaries, and optimization details. A feedback learning unit stores development outcomes and user feedback to enhance future code generation, testing, debugging, and optimization. The invention reduces manual effort, minimizes software defects, accelerates development, and improves software quality.
Disclaimer: Curated by HT Syndication.
