SRA is an enterprise-grade, AI-orchestrated ecosystem designed to formalize the software requirements engineering lifecycle. By combining Large Language Model (LLM) reasoning with rigorous architectural standards, SRA transforms fragmented project visions into high-fidelity, production-ready technical specifications (IEEE-830).

Industry research, including PMI and other studies, indicates that a significant portion of project failures, often estimated between 30% and 50%, can be traced back to poor requirements engineering, including unclear documentation, semantic ambiguity, and stakeholder misalignment. SRA mitigates this risk by providing an automated, multi-layered validation and synthesis engine.

• Zero-Ambiguity Intake: Standardizes raw stakeholder descriptions into structured architectural models.
• AI-Driven Governance: Real-time logic checking to identify contradictions, missing logic, and technical gaps.
• High-Fidelity Visuals: Automated generation of multi-level Data Flow Diagrams (DFD) and system-level Mermaid diagrams.
• Semantic Intelligence: Leverages vector-based knowledge retrieval (RAG) and Graph-Hybrid Search to ensure consistency across complex project portfolios.
• Intelligent Requirement Recycling: Proactively suggests high-quality requirement fragments from past "Gold Standard" projects to accelerate new SRS drafting.
• Objective Quality Auditing: Real-time scoring against the 6Cs of Requirements Quality (Clarity, Completeness, etc.).
• Industry Benchmarking: Integrated RAG evaluation for Faithfulness and Answer Relevancy.

SRA operates on a proprietary 5-layer pipeline that ensures every requirement is processed through a rigid quality-control sequence.

graph TD
    subgraph "Cloud Analysis Layer (SRA Platform)"
        L1[<b>Layer 1: Strategic Intake</b><br/>Unstructured Input Mapping]
        L2[<b>Layer 2: MAS Analysis</b><br/>PO, Architect, & Dev Agents]
        L3[<b>Layer 3: Objective Review</b><br/>6Cs Audit & RAG Evaluation]
        L4[<b>Layer 4: Refinement Hub</b><br/>Live Workspace & Diff Tracking]
        L5[<b>Layer 5: Knowledge Persistence</b><br/>Semantic Indexing & Hybrid Search]
        
        Reliability[(<b>Reliability Layer</b><br/>360s Timeout & Jittered Retries)]
        L2 & L3 -.-> Reliability
    end

    subgraph "Local Execution Layer (CLI Toolkit)"
        CLI["SRA CLI (@sra-srs/sra-cli)"] -->|Auth/Sync| L1
        CLI -->|Verify| Code[(Local Source Code)]
        Code -->|Verification Data| CLI
        CLI -->|Push Audit Trail| L4
    end

    Stakeholder((Stakeholder)) -->|Raw Vision| L1
    L1 --> L2
    L2 --> L3
    L3 -->|FAIL: Poor Score| L2
    L3 -->|PASS| L4
    L4 -->|Export| Artifacts[IEEE SRS, PDF, DFD, API Spec]
    L4 --> L5

• IEEE-830 v1.1.0 Compliance: Automated generation with strict identifier governance and academic prose discipline.
• 6Cs Quality Audit: Automated scoring for Clarity, Completeness, Conciseness, Consistency, Correctness, and Context.
• RAG Benchmarking: Real-time evaluation of LLM Faithfulness and Answer Relevancy.
• User Story Evolution: Generates "Jira-Ready" user stories with granular acceptance criteria.

• Multi-Level DFDs: Generates Level 0 (Context) and Level 1 (Functional Decomposition) Gane-Sarson diagrams.

• Interactive Explorer: Powered by @xyflow/react with support for high-fidelity PNG Export.

• Self-Healing Diagrams: Integrated Mermaid Repair Engine that identifies and fixes syntax errors in generated UML.

• Proactive PII Redaction: Automated sanitization of user intent (Emails, Phone, CC) before processing by external AI providers.
• RBAC Architecture: Secure access control with JWT integration and social OAuth (Google/GitHub).
• Revision History: Complete versioning system with visual diff tracking between requirement updates.
• Audit-Ready Exports: One-click professional PDF generation with table of contents and revision logs.

• Spec-to-Code Traceability: Direct link between cloud requirements and local source code implementations.
• Local Compliance Engine: Run sra check locally to verify that your code matches the official specification.
• Automated Sync: One-command synchronization of requirements into your developer workspace.
• System Diagnostics: Professional sra doctor utility for environment validation and connectivity troubleshooting.
• Reverse Engineering: Beta support for generating requirements directly from existing codebases.

SRA is engineered for stability, security, and enterprise-grade performance.

• Multi-Stage Docker Builds: Minimized production images using separate build/runtime environments.
• Non-Root Execution: Containers run as unprivileged users (nodejs/nextjs) to mitigate security risks.
• Dependency Pinning: Strict versioning of core dependencies (e.g., Next.js 16.1.6) to ensure environment parity.

• Hardened CSP: Strict Content Security Policy injected via Next.js and Express security headers.
• HSTS & Frame Protection: Production-grade Strict-Transport-Security and X-Frame-Options (DENY/SAMEORIGIN) enforcement.
• Secure Session Management: JWT-based authentication with secure cookie handling.
• Privacy Sanitization: Integrated sanitizer.js layer to prevent data leakage to LLM providers.
• Distributed Rate Limiting: Redis-backed throttling ensures global protection across all server instances.

• AI Reliability Layer: Implemented a standardized BaseAgent with a 6-minute timeout, jittered retries, and high-fidelity JSON parsing logs for stable long-form document generation.
• Frontend Code Splitting: Transitioned to an "Archive-First" dynamic loading strategy using next/dynamic. Components like ResultsTabs and their individual sub-tabs are lazy-loaded to minimize initial JS payload and improve TBT.
• Redis Caching: High-traffic endpoints (Dashboard) cached via Upstash for sub-millisecond retrieval.
• Automated SEO: Dynamic sitemap.xml and robots.txt generation for search engine discoverability.
• Graceful Shutdown: Native handling of SIGTERM/SIGINT to ensure zero-downtime deployments.
• Standalone Mode: Next.js optimized standalone output.
• Smart Data Fetching: SWR-based caching and background revalidation.

• Automated Encrypted Backups: Weekly automated database backups with AES-256-GCM encryption.
• Point-in-Time Recovery: 7-day PITR via Supabase for granular data restoration.
• CLI Backup Management: Command-line tools for manual backup creation, restoration, and verification.
• Multi-Location Storage: Backups stored locally, in GitHub Artifacts, and Supabase snapshots.
• Integrity Verification: SHA-256 checksums ensure backup file integrity.

• Comprehensive Audit Logging: Tracks all sensitive operations (create, delete, export) with full metadata.
• Threat Detection: Real-time monitoring for brute force attempts, mass deletions, and unusual access patterns.
• Field-Level Encryption: PII data encrypted at rest using AES-256-GCM.
• Daily Security Audits: Automated dependency scanning, secret leak detection, and security header validation.
• Compliance Ready: Audit trails and security reports for regulatory compliance.

SRA leverages professional GitHub Actions for continuous quality assurance and operational excellence.

• Automated Docker Builds: Multi-stage Docker builds triggered on every push to main, publishing optimized images to GHCR.
• Bundle Size Monitoring: Tracks and reports JavaScript bundle size changes for the Next.js frontend, preventing performance regressions.
• Linting & Formatting: Enforces consistent code style and catches potential errors early in the development cycle.

• Scheduled Health Checks: Hourly automated uptime verification of the entire SRA pipeline.
• Real-time Observability: Dedicated /api/health endpoint for deep system diagnostics (DB, AI Provider).
• Docker Healthchecks: Infrastructure-aware readiness probes ensure the frontend only serves traffic once the backend is fully initialized.
• CodeQL Security Scans: Proactive identification of security vulnerabilities and common coding errors.
• Dependency Vulnerability Checks: Scans for known vulnerabilities in project dependencies.
• Automated Backup Verification: Weekly encrypted database backups with integrity validation.
• Daily Security Audits: Comprehensive security posture checks including secret leak detection and permission audits.

SRA uses Terraform to manage cloud infrastructure declaratively, ensuring reproducibility, disaster recovery, and version-controlled infrastructure changes.

terraform/
├── main.tf                    # Provider & backend configuration
├── variables.tf               # Variable definitions
├── vercel.tf                  # Vercel project resources
├── outputs.tf                 # Output values
├── terraform.tfvars.example   # Configuration template
└── README.md                  # Detailed usage guide

# Navigate to terraform directory
cd terraform

# Initialize Terraform
terraform init

# Preview infrastructure changes
terraform plan

# Apply changes (when ready)
terraform apply

# Pull and run the latest images via Compose
docker compose up --build -d

npm install -g @sra-srs/sra-cli
sra init

# Install dependencies across all workspaces
npm install

# Initialize Identity & Data
npm run dev:backend

# Or run everything concurrently
npm run dev:all

SRA/
├── .github/                # CI/CD Workflows (Lint, CodeQL, Stale)
├── .agent/                 # Agent workflows and skill definitions
├── backend/                # API Engine & Node.js orchestration workspace
│   ├── prisma/             # Schema & Migrations
│   ├── src/                # Services, controllers, and core AI logic
├── frontend/               # Next.js 16 Application workspace
│   ├── app/                # Server-driven App Router
│   ├── components/         # High-fidelity React components
├── cli/                    # SRA Toolkit npm workspace
├── model/                  # AI Model and testing workspace
├── terraform/              # Infrastructure as Code (Platform config)
├── docs/                   # Documentation & Security policies
└── package.json            # Root monorepo workspace definition

• v2.0: Strategic 5-Layer Pipeline Implementation.
• v2.1: Interactive DFD Explorer & PNG Export.
• v2.2: GitHub CI/CD & Agentic Automation.
• v3.0: SWR Data Fetching & Backup Automation.
• v3.0: Enterprise Security Monitoring & Audit Logging.
• v3.1: Distributed Rate Limiting & Load Balancing.
• v3.2: Industry Benchmarking & MAS Refinement.
• v4.0: Full CLI Toolkit & Spec-to-Code Traceability.
• v4.5: Collaborative Real-time Multi-User Editing.
• v5.0: Custom Model Fine-tuning (MLOps integration).

We welcome contributions from the community. Please review our Contribution Guidelines and Governance Policy for architectural context and coding standards.

To report vulnerabilities, please contact the security team via the repository's security advisory tab.

This project is licensed under the Apache License 2.0. See the LICENSE file for the full legal text.