CSCI 151 - Lab 11
Text Prediction


In this lab, we will implement a Trie for storing Strings and use it to predict words as they are being typed.



  1. Download the skeleton for this project.
  2. Unpack the code into a new Eclipse Java project.


Modern smartphones include keyboard assistants that will suggest words while you are typing. There are many data structures that can be used to assist in this interaction, to predict the remainder of words, and autocorrect typed words. One such data structure is a Trie, which divides the words into their component characters, and then stores the words in a minimal way based on their overlapping characters. There are two main pieces to the model of our code, a Trie to capture these characters in a tree-like structure, and a SortedArray to store the list of children in sorted order.

Methods that remain to be implemented in the SortedArray and Trie classes have been marked with TODO for easy identification.

Step 1 - SortedArray

We wish to encapsulate an ArrayList, to add the functionality of being sorted, while preventing a user from accidentally adding new nodes in an unsorted fashion. Most of our methods will be mere wrappers for the corresponding ArrayList methods, except the insert method, which should implement an insertionSort algorithm.

Step 2 - size

To gain familiarity with the different components of the lab, first write a method for a Trie that will return the number of words contained in a given Trie.

Step 3 - getChildWith

The getChildWith method should use the functionality of the SortedArray to perform a linear search for a child Trie corresponding to the given character. If a matching child Trie is not found, this method should return null.

Step 4 - contains and add

Complete the contains and add methods of the Trie. Contains ask the question: Is the given value a suffix of this Trie? Walk through the tree, moving down to the appropriate child for each character in value. If you fall off the tree, return false, otherwise return true when the last child is contained in the Trie.

Add is implemented in a similar manner. Walk through the value, and add a new chain of Trie nodes, one for each letter that is not already found in the Trie. Mark the last Trie node as contained.

Step 5 - remove

Complete the method to remove a word from the Trie. This method should walk down the tree, following the appropriate child, and save the parent if there are other viable paths or if the parent is the end of another word. Unmark the last node. Then if it was an only child, remove the unneeded chain of nodes from the last good parent.

Step 6 - Predicting the Text

Our algorithm for prediction is simple. As a user types in text, the Trie will need to search for all words that can be made using what the user is typing as a prefix. You will write two methods that can be used in this way.

First, the inorder method will return an ArrayList of all possible words to be created from a given Trie node. If the node is in the middle of the Trie, it will only be returning suffixes.

Second, the successorsTo method will return an ArrayList of all possible words to be created following a given prefix. The prefix should be included in the words returned.

What to Hand In

Submit your and Trie implementations.


© Mark Goadrich, Hendrix College