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Software Engineering

RentWise — Smart Rental & Resource Management

A rental management platform using the Gale–Shapley stable matching algorithm to fairly pair tenants with properties.

Difficulty — advanced Complexity — 7/10 Category — Software Engineering
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Overview

RentWise digitizes property operations — tenant handling, payment tracking, and allocation — for urban rental markets. What separates it from a typical CRUD rental app is the matching engine: tenant-property allocation is solved as a stable matching problem rather than first-come-first-served, so both sides' preferences are respected.

Architecture

A Singleton-controlled modular system spanning property/tenant management, a request-processing queue, a stable-matching allocation engine, and a payment/analytics layer — built on classic data structures (linked lists, stacks, queues, hash maps, trees, graphs).

Key Features

  • Gale–Shapley stable matching for tenant-property allocation under competing preferences.
  • Queue-based priority scheduling for incoming rental requests.
  • Automated payment tracking and notification system.
  • Data-driven reporting for landlord decision-making.

Development Process

  • Modeled tenants and properties as two preference-ranked sets before implementing any matching logic.
  • Implemented Gale–Shapley directly against the domain model rather than as an abstract algorithm demo.
  • Layered priority-queue request handling on top of the completed matching engine.
  • Added payment tracking and reporting as the final application layer.

Challenges & Solutions

Challenge

Naively matching tenants to properties by request order ignored genuine preference conflicts between multiple qualified tenants.

Solution

Applied Gale–Shapley stable matching so no tenant-property pair could mutually prefer each other over their assigned match — a fairness guarantee, not just an allocation rule.

Results & Impact

The platform produces allocations that are provably stable under the Gale–Shapley guarantee, while automated payment tracking and reporting reduce the manual overhead typical of small-scale property management.

Future Improvements

  • Add a weighted-preference variant for tenants with hard constraints (budget, location).
  • Build a tenant-facing web portal.
  • Extend analytics to vacancy forecasting.