Automated Requirements Traceability & Verification Validation Engine

📌 Project Overview

This repository contains a production-ready engineering compliance and systems engineering audit tool implemented in Python. In high-reliability industrial domains (such as aerospace, defense, automotive, and medical devices), complex systems cannot be deployed without proving that every high-level system requirement is actively mapped to a corresponding hardware block and verified via physical testing. This project acts as a lightweight Model-Based Systems Engineering (MBSE) validation engine—utilizing regular expressions (Regex) and relational data structures to automatically parse unstructured engineering documentation, build a functional traceability graph, and flag structural compliance vulnerabilities.

⚡ Technical Architecture

The engine compiles, cross-references, and audits system integrity across three distinct computational layers:

• Engineering Data Ingestion: Parses distinct configuration data tables representing system-level operational requirements (e.g., input voltage tolerances, antenna counts) and hardware validation engineering test logs.
• Regex-Driven Dependency Mapping: Deploys regular expression string extraction pattern-matching matrices to scan free-text verification descriptions, extracting target structural reference handles (REQ-XXX) to establish relational link associations.
• Deterministic Verification Audit: Performs a relational left join across data spaces to generate an automated structural compliance ledger. It categorizes the architectural status of each system component into one of three distinct compliance tracks:
  1. Fully Compliant: A test plan is mapped, and the hardware testing status reads PASSED.
  2. Failing Trace: A test plan is mapped, but the hardware fails to satisfy compliance thresholds (FAILED).
  3. Untested Gap (Red-Flag): High-level requirements exist, but no hardware validation mapping can be programmatically detected.

📊 Compliance Audit & Metrics Profile

The architectural health of a mock high-reliability hardware configuration was audited by the verification pipeline:

• Component Level Audit: The bar graph tracks individual components, immediately isolating unverified dependencies (REQ-002 Overcurrent Protection and REQ-005 Emergency Cutoff) from failing operational modules (REQ-004 Thermal Dissipation).
• System-Wide Compliance State: The system diagnostic reports that only 40.0% of the project design is fully compliant, warning engineering managers of a 40.0% coverage gap in unmapped requirements and a 20.0% integration test failure rate.

🛠️ How to Replicate

1. Launch the file notebooks/requirements_traceability_engine.ipynb inside Google Colab.
2. Execute the processing cells sequentially to build the data baselines, run the regex parser, and compute the structural mappings.
3. The script outputs a text-based compliance ledger to the console and saves the high-resolution tracking graphics to your environment.

📂 Repository Structure

├── notebooks/          # Interactive Colab notebooks containing compliance algorithms
├── assets/             # Exported system compliance pie charts and audit plots
└── README.md           # Professional project documentation