Wordle Solver
Information theory-based Wordle solver achieving 80% success within 4 attempts
Project Overview
When Wordle went viral in late 2022, I saw an opportunity to apply information theory and algorithmic thinking to create an optimal solver. The result was a system that outperforms the average human player by a significant margin.
Built as my first full-stack application, this project taught me the fundamentals of React.js, Firebase deployment, and algorithm optimization. The solver uses a three-phase strategy that maximizes information gain from each guess, converging on the solution within 4 attempts in 80% of cases.
Won Popular Vote at RoboHackIT 2022 for combining technical depth with an intuitive, engaging interface.
Wordle Solver Demo
The Algorithm
The solver implements a three-phase strategy grounded in information theory:
Phase 1 - Information Maximization:
The algorithm opens with "AUDIO" and "CREST" - a carefully selected pair that covers all five vowels and 8 of the 10 most common English letters. These two guesses alone provide massive information about letter presence and position.
Phase 2 - Adaptive Mapping:
After each guess, the system analyzes the color-coded feedback to build a probabilistic model of remaining word candidates. Rather than random guessing, it calculates which word will maximize expected information gain - essentially asking "which guess eliminates the most possibilities regardless of the answer?"
Phase 3 - Convergence:
As the possibility space narrows, the algorithm switches from information maximization to direct elimination, using frequency analysis and common word patterns to identify the final answer. This approach achieves the solution within 4 attempts in 80% of cases - significantly better than the ~60% success rate of average players.
Technical Implementation
This was my first experience building a full-stack application:
Frontend: React.js with custom components mimicking Wordle's interface
Algorithm Engine: JavaScript implementation of information-theoretic word selection
Word Database: Optimized data structures for sub-second candidate filtering from 12,000+ valid words
Deployment: Firebase hosting for both frontend and backend logic
Performance: Real-time guess recommendations with <100ms response time
The project forced me to think about scalability, state management, and user experience - lessons that carried into every subsequent project.
Impact & Recognition
RoboHackIT 2022 - Popular Vote Winner
The project resonated with both judges and attendees, winning the Popular Vote award. What made it successful wasn't just the algorithm - it was making complex algorithmic thinking accessible and demonstrating measurable improvement over human performance.
Performance Metrics:
80% success rate within 4 attempts
95% success rate within 5 attempts
Average 3.7 guesses per puzzle
Consistently outperforms average players by 20%+ success rate
The solver proved that well-applied algorithms can achieve systematic advantages over intuition-based approaches, a lesson I've applied to every subsequent project.
Skills & Technologies
Project Info
October 2022 - October 2022
Completed