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Full-Stack case study

Centralized LMS

Spring Boot + React learning management prototype (AI-assisted)

Full-StackPrototypeSource code (opens in a new tab)
Commits
9

in the repository

Build window
2 days

3 Mar 2026 to 4 Mar 2026

Lines of code
1,727

hand-written source

Technologies
8

in the stack

01

Overview

A learning management prototype covering login, students, courses, enrollments, assignments and grading, attendance, certifications and a statistics dashboard. Built over two days as an AI-assisted prototype using Codex pull requests.

Goal. Explore how institutions could unify logins, enrollment, attendance, assessments and certification in one portal.

My role

AI-assisted prototype (Codex pull requests)

02

What it does

  • 01Register, login and profile endpoints with BCrypt-hashed passwords
  • 02Students, courses and enrollments with duplicate protection
  • 03Assignments, submissions and grading with score limits
  • 04Attendance logs restricted to PRESENT, ABSENT or LATE
  • 05Certificates issued with a unique code when the score threshold is met
  • 06Dashboard statistics endpoint; Dockerfiles and Docker Compose
03

Architecture

CLIENTSPRING BOOT APIDATAReact + ViteDashboard UIControllers/api endpointsLmsServiceBusiness rulesSpring Data JPAEight entitiesMySQL 8Docker Compose
A standard layered Spring Boot service over MySQL, fronted by a small React dashboard.
04

Engineering decisions

Business rules in the service layer

Rules such as one certificate per student per course and submissions only for enrolled students are enforced in LmsService.

05

Tech stack

  • Java 17
  • Spring Boot
  • Spring Data JPA
  • MySQL
  • React
  • Vite
  • Docker Compose
  • BCrypt
06

Timeline

  1. 3 Mar 2026

    Initial commit and first AI pull request

    Repository created; first pull request from a Codex branch merged.

  2. 4 Mar 2026

    Full LMS merged

    Auth, attendance, assessments, certifications and dashboard merged through further pull requests.

07

Scope and next steps

  • Built over 3–4 March 2026 as a rapid prototype with AI assistance.
  • Not deployed.

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