MUMBAI, India, Feb. 13 -- Intellectual Property India has published a patent application (202611000256 A) filed by Nidhi Sharma, Prayagraj, Uttar Pradesh, on Jan. 2, for 'system and method for quantum assured deterministic multi-phase code assurance with ai-governed compliance crosswalks, cryptographic evidence chaining, and dual pipeline execution.'
Inventor(s) include Nidhi Sharma.
The application for the patent was published on Feb. 13, under issue no. 07/2026.
According to the abstract released by the Intellectual Property India: "The present invention relates to a deterministic software code assurance system for regulated software deployments, wherein code-security findings and compliance artifacts are produced under reproducible, verification-gated execution rather than probabilistic inference. The system integrates quantum-implemented optimization, multi-model language processing, and automated AI governance to provide comprehensive vulnerability detection and unified regulatory compliance mapping across multiple frameworks with auditable evidence trails, while maintaining operational continuity via a hybrid runtime that supports offline execution when AI services are unavailable or rejected. [505] The invention introduces an advanced code analysis architecture that includes one (1) central language model (CLM) configured to orchestrate fourteen (14) specialized nano language models (NanoLMs) under strict policy-gated governance constructs. This governance layer enforces specific high-fidelity trained model artifacts validated for high-precision detection performance. The architecture further includes a quantum-implemented optimization subsystem (executing quantum algorithms such as QAOA and SA-QT within a quantum computation framework) which is rigorously wrapped in a Mathematical Certainty Layer utilizing formal verification (e.g., Lean theorem proving) to collapse probabilistic quantum outputs into deterministically proven, regression-free artifacts. This subsystem is coupled with deterministic cross-checking and governance-mandated parity validation, and an automated compliance crosswalk engine configured to map findings into over 20 regulatory standards (across 250,189 compliance parameters) with cryptographically chained, tamper-evident evidence records. [510] The system architecture centers on a 'Dual Pipeline' workflow comprising two distinct structures: (1) A Six-Phase Offline Training Pipeline used for machine learning model generation; and (2) A Six-Phase Production Pipeline used for real-time software verification. Both pipelines execute a unified schema of six core phases: (i) Static Analysis; (ii) Security Assessment; (iii) Quality Evaluation; (iv) Maintainability Review; (v) Performance Analysis; and (vi) Refactoring Suggestions. These parallel pipelines are unified under an eleven-phase orchestration sequence that manages advanced compliance and remediation."
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