DefectXray is a cloud-based, standalone product designed to revolutionize defect management within enterprise CI/CD and testing workflows. The platform provides automated defect severity classification (Low, Medium, High) and integrates Orthogonal Defect Classification (ODC) attributes to offer actionable insights for prioritizing defect resolution. By analyzing defects across the software stack—UI, backend, and database—DefectXray empowers enterprises to enhance software quality, streamline development processes, and optimize developer productivity.
The Minimum Viable Product (MVP) focuses on core severity classification and basic ODC integration (Defect Type and Trigger), with a robust reporting dashboard, API endpoints for CI/CD integration, and a scalable architecture for future enhancements. The project targets a beta release in November-December 2025 and a full public launch by January 2026.
- Severity Classification: Automatically classify defects into Low, Medium, and High severity levels based on predefined rules and ODC attributes, enabling effective prioritization in enterprise CI/CD pipelines.
- ODC Integration: Incorporate ODC attributes (Defect Type and Trigger) to provide process feedback, identifying areas for improvement in the development lifecycle.
- Actionable Reporting: Offer a user-friendly dashboard to visualize defect distributions by severity and ODC attributes, supporting data-driven decision-making.
- CI/CD Workflow Integration: Provide seamless integration with enterprise CI/CD tools through CLI and API endpoints, ensuring defect data is accessible and actionable within existing workflows.
- Defines deterministic rules for mapping defect characteristics and ODC attributes (Defect Type, Activity) to severity levels.
- Incorporates configurable weights (e.g., Defect Type 70%, Activity 30%) and custom keyword configurations for enterprise adaptability.
- Targets 80% precision in severity classification through validation with real-world defect datasets.
- Designs a robust database schema to store defect data with fields for severity (enum: High, Medium, Low), ODC attributes (Defect Type, Trigger), and metadata.
- Implements indexes for performance optimization and ensures data integrity with constraints and default values.
- Supports scalability for enterprise data volumes with efficient querying capabilities.
- Ingests defect data from enterprise tools (e.g., Jira, Sentry) via APIs and manual uploads (CSV, JSON).
- Normalizes data into a unified format aligned with the PostgreSQL schema, applying heuristic rules for initial ODC mapping.
- Designed for scalability, targeting 1,000 defects/hour with a <5% error rate in metadata mapping.
- Implements a rules-based engine to classify defects based on ODC attributes and predefined logic from Task 1.
- Supports enterprise customization through configurable severity mappings and handles incomplete data with fallback logic.
- Integrates with PostgreSQL to update defect records with final classifications for reporting.
- Develops an interactive, React-based dashboard with Tailwind CSS for visualizing defect severity and ODC metadata distributions.
- Features filtering, drill-down capabilities (e.g., view details for High severity defects), and CSV export for usability.
- Optimizes performance for large datasets (target: <2-second load time for 10,000 defects) with pagination and data aggregation.
- Provides secure RESTful endpoints using Node.js/Express for defect data ingestion (POST /defects) and retrieval (GET /defects with filters).
- Implements OAuth 2.0 authentication with specific scopes (defects:read, defects:write) and rate limiting (default 100 requests/minute).
- Targets high throughput (1,000 requests/minute with <100ms latency for 90% of calls) for enterprise scalability.
- Frontend: React with Tailwind CSS for the reporting dashboard, hosted on a CDN for fast access.
- Backend: Node.js with Express for API endpoints, handling defect ingestion and retrieval.
- Database: PostgreSQL for storing defect metadata and classifications, with indexes for performance.
- Cloud Infrastructure: Deployed on Azure using Azure Kubernetes Service (AKS) for scalability and Azure Blob Storage for artifacts.
- Security: OAuth 2.0 for authentication, TLS 1.3 for data in transit, and AES-256 encryption for sensitive data at rest.
- Planning and Design: May-June 2025 (1 month) - Requirements definition and architecture design.
- Core Development: June-October 2025 (4 months) - Implementation of MVP components (Tasks 1-6).
- Testing and Beta Release: October-December 2025 (2 months) - Internal testing and private beta with enterprise clients.
- Public Release: December 2025-January 2026 (1 month) - Full launch with marketing and free trial offerings.
- Free Tier: Basic defect classification for up to 50 defects/month.
- Paid Tier 1: $1,000/month per team for unlimited classification and CI/CD integration.
- Paid Tier 2: $3,000/month per team for classification plus fix recommendations.
- Enterprise Tier: Custom pricing starting at $20,000/month for on-premises deployment and dedicated support.
As DefectXray is under active development, detailed setup instructions and documentation will be provided closer to the beta release. For now, explore the project structure and task definitions in the tasks/ directory to understand the components being built.
Contributions are welcome once the beta phase begins. Please check back for guidelines on how to contribute to DefectXray's development.
This project is licensed under the terms specified in the LICENSE file.
For inquiries or to express interest in the beta program, please contact the project team (details to be provided closer to beta release).
DefectXray - Empowering enterprises to prioritize and resolve defects with precision.