Bug Tracker System
An agile project management and issue-tracking platform built on React.js, Spring Boot, and PostgreSQL. Features role-based ticket lifecycles, real-time comment threads, and LLM-powered bug analytics.
Managing modern software lifecycles requires structured tracking. The Bug Tracker System enables teams to map issues, assign tasks, log status histories, and inspect audit logs under strict security contexts.
Core Architecture & Capabilities
Engineered to manage ticket lifecycles, project details, and security roles seamlessly.
⚛️ React Frontend
Provides a clean dashboard showing project details, kanban ticket boards, user filters, and responsive ticket details view.
🚀 Spring Boot APIs
Exposes REST endpoints configured with pagination, security validations, and criteria query execution adapters.
🐘 PostgreSQL Datastore
Maintains robust relational storage mapping projects, bugs, audit logs, and security profiles securely.
🔑 JWT Stateless Security
Uses JSON Web Tokens (JWT) for secure authentication, locking down backend APIs against unauthorized operations.
👥 Role-Based RBAC
Applies granular permissions segregating Admin dashboard features, Developer ticket editing, and QA Reporter submissions.
🤖 AI-Assisted Analysis
Uses natural language parsing models to inspect bug logs, suggest potential code origins, and recommend developers.
Relational Database Layout & Ticket Security
🔄 Immutable Ticket Audit History
Appends transaction audit items capturing previous and new values during any ticket update. Ensures changes are trackable for reporting.
🏷️ Dynamic Spring Data Specifications
Powers flexible multi-parameter ticket search filtering (by priority, status, projects, and users) without compiling duplicate SQL scripts.
📊 Pagination & Data Loading
Implements server-side query paging for log feeds, avoiding loading entire data blocks and keeping front-end render times low.
Key Engineering Breakthroughs
State Invalidation on Simultaneous Ticket Modification
The Problem: In active team workspaces, two developers might open and edit the same bug ticket concurrently. The developer who saves last silently overwrites the changes made by the first, leading to data loss.
The Solution: Implemented **Optimistic Locking** using a versioning schema. Added a @Version column to the ticket entity. If a transaction attempts to write a record with an outdated version timestamp, JPA automatically rolls back the transaction and throws an exception, alerting the user to reload the ticket state.
Laggy Search Performance on Multi-Criteria Grid Queries
The Problem: Compiling queries with dynamic combinations of 5+ filters (Project, Assignee, Priority, Status, Creation Date) generated highly inefficient SQL execution paths in PostgreSQL, lagging page loads under large datasets.
The Solution: Restructured search indexes. Built composite, multi-column **B-Tree database indexes** matching common user filter query combinations, and set explicit database fetch bounds, dropping query execution time by 85%.
Interested in the code?
Explore the complete React frontend components, Spring Boot security controllers, and PostgreSQL database schemas on GitHub.