📌 Overview A C++ implementation of an auto-complete system using the Trie data structure. This project provides real-time word suggestions as the user types, with multiple sorting options (frequency, length, lexicographical order). It supports dynamic dictionary updates, case insensitivity, and robust error handling.
✨ Features ✔ Prefix-based suggestions – Get word completions in real-time. ✔ Multiple sorting methods:
Frequency-based (most searched words first)
Shortest-first (BFS traversal)
Lexicographical order (DFS traversal) ✔ Dynamic dictionary management:
Add new words
Delete existing words
Auto-save changes to file ✔ Case-insensitive matching – Works with "Car", "CAR", or "car". ✔ Exact match highlighting – Bold or colorize exact matches. ✔ Error handling – Handles invalid inputs gracefully.
📂 Project Structure AutoComplete_Project/ ├── src/ # Source code
│ ├── Trie.cpp # Trie implementation
│ ├── Trie.h # Trie header
│ ├──AppStart.cpp # Core logic
│ ├──AppStart.h #Core header
│ ├── AutoComplete.cpp #The main function
│ ├── main.cpp # CLI interface
├── data/ # Dictionary files
│ └── dictionary.txt # Default word list
│ └── searchedWord.txt # The words that the user searched about
└── README.md # This file
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Entering a Prefix Enter a prefix: ca Choose sorting method:
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Frequency (default)
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Shortest-first (BFS)
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Lexicographical (DFS) => 2
Output: car cat care cart -
Adding/Deleting Words Options:
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Search suggestions
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Add a word
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Delete a word
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Display Dectionary
2 Enter word to add: coffee "coffee" added successfully!
🔧 Extending the Project
- GUI Integration: Use Qt or ImGui for a graphical interface.
- Persistent Frequency Tracking: Store word frequencies in a file.
- Multilingual Support: Extend for non-English characters.
🤝 Contributers
- Gehad Ebrahim
- Tassnim Shellah
- Habiba Osama
- Lina Hisham
- Dalia Ahmed
- Sondos Khalid
- Sara Mohsen
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🔍 Why Trie? The Trie data structure is ideal for auto-complete because: ✅ Fast prefix searches – O(L) where L is the length of the prefix. ✅ Memory-efficient – Shares common prefixes among words. ✅ Scalable – Handles large dictionaries efficiently.