🎓 CS-499 Computer Science Capstone Portfolio

Animal Shelter Management System | SNHU CS-499 Capstone Project

Demonstrating Comprehensive Computer Science Skills Through Full-Stack Development

📱 View Static Demo 💻 View on GitHub 🏠 Back to Portfolio

📋 Table of Contents

Project Overview
Live Demo
Course Outcomes
System Architecture
Key Features
Performance Results
Getting Started
Project Structure
Documentation
Author

🎯 Project Overview

The Animal Shelter Management System is a comprehensive full-stack application that demonstrates mastery of computer science principles through progressive enhancement of a single artifact. Originally developed for CS-340: Client/Server Development, this project was enhanced across three key categories as part of the CS-499 Capstone:

Software Design & Engineering (Milestone 2): Complete CRUD implementation with professional error handling
Algorithms & Data Structures (Milestone 3): Advanced algorithms for caching, sorting, and data analysis
Databases (Milestone 4): Production-grade database optimization and management

The system provides a complete dashboard for managing animal shelter operations, tracking adoptions, and analyzing trends with real-time visualizations.

🌐 Live Demo

Static Demo Page: View Demo

Note: For full interactive functionality with database operations, clone and run locally.

🎓 Course Outcomes

This project comprehensively addresses all five CS-499 course outcomes:

Outcome	Demonstration
1. Collaborative Environments	Designed for team collaboration with clear modular architecture and comprehensive documentation
2. Professional Communication	Professional code documentation, video code review, and detailed technical narratives
3. Algorithmic Solutions	Implemented efficient algorithms (O(log n) search, O(n log n) sorting, LRU caching)
4. Well-Founded Techniques	Industry-standard database optimization, modern web development practices, and comprehensive testing
5. Security Mindset	Input validation, secure configuration management, and defensive programming throughout

🏗️ System Architecture

Web Browser → Flask Web Server → Enhanced CRUD Module → MongoDB Database
                   ↓                    ↓                    ↓
           Software Design      Algorithms      Database Optimization

Enhancement Categories:

Software Design: Complete CRUD, error handling, security
Algorithms: Caching, sorting, analysis, search
Databases: Indexing, aggregation, validation, performance

✨ Key Features

🔧 Software Design & Engineering

Complete CRUD Operations: Full create, read, update, delete functionality
Professional Error Handling: Comprehensive exception management and logging
Security Implementation: Environment-based configuration and input validation
Modular Design: Clean separation of concerns and reusable components

🧮 Algorithms & Data Structures

LRU Caching System: Configurable cache with TTL and eviction policies (O(1) operations)
Sorting Algorithms: Merge sort and quicksort implementations with custom comparators
Data Analysis: Real-time adoption trend analysis with statistical aggregation
Search Algorithms: Binary search implementation (O(log n) complexity)

🗄️ Database Optimization

Advanced Index Management: Automated index creation based on query patterns
Aggregation Pipelines: Complex data processing entirely within MongoDB
Schema Validation: JSON schema enforcement for data integrity
Performance Analysis: Query explanation with optimization recommendations
Backup/Restore: Full data preservation and recovery capabilities

📊 Performance Results

Operation	Before Optimization	After Optimization	Improvement
Basic Queries	100ms	5ms	20× faster
Complex Aggregations	500ms	50ms	10× faster
Cached Repeated Queries	50ms	2ms	25× faster
Full-Text Search	Not Available	20ms	New capability
Connection Overhead	100ms	40ms	60% reduction

🚀 Getting Started

Option 1: Run Locally (Full Functionality)

Prerequisites

Python 3.8+
MongoDB (optional for full functionality)
Git

Installation

Clone the Repository

git clone https://github.com/annjessicatan/annjessicatan.github.io.git
cd annjessicatan.github.io/capstone-project/animal-shelter-system

Set Up Virtual Environment

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

Install Dependencies
```
pip install -r requirements.txt
```

Configure Environment Variables

cp .env.example .env
# Edit .env with your MongoDB credentials (optional)

Run Tests
```
python run_all_tests.py
```
Start the Application
```
python app.py
```
Access the Dashboard
Open your browser and navigate to http://localhost:5000

Option 2: View Static Demo

For a quick preview without running locally, visit:
📱 Static Demo Page

Note: The static demo uses mock data. For full functionality with real database operations, run locally.

📁 Project Structure

~/capstone/annjessicatan.github.io/                    # MAIN REPOSITORY (48KB total)
│
├── 📄 README.md                                      # Portfolio README (9.7KB)
├── 🏠 index.html                                     # Portfolio homepage (1.4KB)
├── 🚫 .gitignore                                     # Git ignore rules (0.7KB)
│
└── 📁 capstone-project/
    │
    └── 📁 animal-shelter-system/                     # CAPSTONE PROJECT FOLDER
        │
        ├── 🐍 TAN_CRUD_Python_Module.py             # MAIN ARTIFACT (50.5KB)
        │   ├── Milestone 2: Software Design Enhancements
        │   ├── Milestone 3: Algorithm Enhancements  
        │   └── Milestone 4: Database Enhancements
        │
        ├── 🌐 app.py                                 # Flask web app (3.3KB)
        ├── 📋 requirements.txt                       # Dependencies (0.5KB)
        ├── 📖 README.md                              # Project README (2.9KB)
        ├── 🧪 run_all_tests.py                       # Test runner (3.6KB)
        ├── 🎮 demo.html                              # Static demo page (5.8KB)
        ├── 🚀 start.sh                               # Startup script (0.1KB)
        │
        ├── 📁 static/
        │   ├── 📁 css/
        │   │   └── 🎨 style.css                     # Dashboard styles (5.5KB)
        │   └── 📁 js/
        │       └── ⚡ dashboard.js                   # Dashboard interactivity (17.1KB)
        │
        ├── 📁 templates/
        │   └── 🖥️ index.html                        # Dashboard template (6.5KB)
        │
        ├── 📁 tests/
        │   ├── 🧮 test_milestone3_fixed.py          # Algorithm tests (7.7KB)
        │   └── 🗄️ test_milestone4_fixed.py         # Database tests (9.3KB)
        │
        ├── 📁 docs/
        │   ├── 📊 test_results.md                   # Test documentation (5.0KB)
        │   └── 📋 TEST_REPORT.md                    # Test report (0.4KB)
        │
        └── 📁 (Supporting files)/
            ├── 📥 import_data.py                    # Data import utility (5.8KB)
            ├── 🔍 query_real_data.py                # Query utility (1.4KB)
            └── 🧪 simple_test.py                    # Simple tests (0.8KB)

📚 Documentation

Comprehensive Documentation Available:

Code Review Video: Detailed walkthrough of enhancements
Test Results: Complete performance benchmarks
Architecture Documentation: System design and decisions
Deployment Guide: Production deployment instructions

Technical Reports:

Milestone 2: Software Design & Engineering enhancements
Milestone 3: Algorithms & Data Structures implementation
Milestone 4: Database optimization and performance analysis
Final Self-Assessment: Comprehensive reflection on the capstone journey

👩‍💻 Author

Ann Jessica Tan
Bachelor of Science in Computer Science
Southern New Hampshire University

Background

Former Physical Therapy professional transitioning to software development, bringing strong analytical skills, attention to detail, and patient-centered problem-solving approach to technology.

Contact

GitHub: @annjessicatan
Portfolio: annjessicatan.github.io
Email: ajessicavtan@gmail.com

Skills Demonstrated

Programming: Python, JavaScript, HTML/CSS
Frameworks: Flask, Chart.js
Databases: MongoDB (PyMongo), SQL
Tools: Git, VS Code, WSL, Jupyter
Methodologies: Agile, Test-Driven Development, CI/CD

📄 License

This project was developed as part of the CS-499 Computer Science Capstone at Southern New Hampshire University. The code is available for educational and portfolio purposes.

🎉 Thank you for visiting my capstone portfolio!

"Transitioning from healthcare to technology, I bring a unique perspective to software development – combining analytical precision with human-centered design."

⭐ Star this repository if you find it helpful!

📱 Demo • 📦 GitHub • 🏠 Portfolio