## MSc Software Workshop, Spring Term 2018-19

### Designed by Seyyed Shah and Uday Reddy

Assigned: Thursday, 7th February, 2019

Intermediate Progress Review : parts 1 and 2, Thursday, 14th February, 6:30pm                  Final Deadline : All Parts, Thursday, 21st February, 9:00pm.

As usual, include in your submission:

2. thorough testing. (You may use JUnit wherever applicable.)

As well as data structures and algorithm complexity, this exercise assesses several concepts taught during the course. If you don’t understand any part of the exercise, please ask course instructors.

Start early. The questions get progressively harder. All work and progress on the exercise must be submitted using Canvas.

Contents

### Introduction

In this worksheet, you will write the algorithms for a sample application using the Java Collection classes. In the next worksheet, you will attach a Graphical User Interface (GUI) to make it a full application. The sample application is that of predictive text.

Before the advent of touch screens, mobile telephones in English-speaking countries used a keypad like this one:

As you notice, there are keys for digits 1–9, used for dialing phone numbers. But these keys were also used to enter letters a–z. When a text message needed to be entered, the keys corresponding to the letters would be used. However, since there are multiple letters on each key, the required letter needed to be disambiguated somehow.

In the basic system without predictive text, the user must press the  appropriate  key  a number of times for a particular letter to be shown. Consider the word “hello”. With this method, the user must press 4, 4, 3, 3, 5, 5, 5, then pause, then 5, 5, 5, 6, 6, 6.

To enter text more easily, the system of predictive text (also called “T9”) was devised. The user presses each key  only once and the mobile phone uses a dictionary to guess what word       is being typed using a dictionary, and displays the possible matches. So the word “hello” can be typed in 5 button presses “43556” without pauses, instead of 13 in the standard system. The numeric string “43556” is referred to as a “signature” of the world “hello”.  If this is the only match,  the user can press space and carry on.  If there are multiple matches,  the user   might need to select one of them before proceeding.

A given numeric-signature may  correspond  to  more  than  one  word.  Predictive  text technology is possible by restricting available words to  those  in  a  dictionary.  Entering  the  numeric signature “4663” produces the words “gone” and “home” in many dictionaries.

In this exercise, you will design and develop a predictive text system. For simplicity, assume that the user does not need punctuation or numerals. You must also limit your solutions to producing only lower-case words.

The final version of your programs should use the words dictionary available with the worksheet on canvas. However, during testing, it is better for you to create a small dictionary file of your own for which you know what outputs to expect.

All the classes in this worksheet should be placed in a package called predictive. Use the class/method names given in the questions.

1 Prototypes and Design (25%)

This part deals with building a “prototype” for the predictive text problem, which is not expected to be efficient, but it will be simple and allow you to compare it with the efficient implementation to be done in later parts.

Write the first two methods in a class named PredictivePrototype inside the package predictive.

1. (5%) :  Write a method wordToSignature with the type:

public static String wordToSignature(String word)

The method takes a word and returns a numeric signature. For example, “home” should return “4663”.  If the word has any non-alphabetic characters, replace them with a “  ” (space) in the resulting signature. Accumulate the result character-by-character.You should do this using the StringBuffer class rather than String. Explain, in your comments, why this will be more efficient.

2. (10%): Write another method signatureToWords with the type:

public static Set<String> signatureToWords(String signature)

It takes the given numeric signature (passed to it as a String) and returns a set of possible matching words from the dictionary (as a Set of Strings). The returned list must not have duplicates and each word should be in lower-case.

The method signatureToWords will need to use the dictionary to find words that match the string signature and return all the matching words.

In this part of the exercise, you should not store the dictionary in your Java program. Explain in the comments why this implementation will be inefficient.

3. (10%): Create command-line programs (classes with main methods) as follows:

Words2SigProto for calling the wordToSignature method, and

Sigs2WordsProto for calling the signatureToWords method.

Each program must accept a list of strings and call the appropriate method to do the conversion.

Hints:

Use the Scanner class to read the dictionary line by line, assuming there is only one word per line.

When reading the dictionary, ignore lines with non-alphabetic characters. A useful helper method to accomplish this would be:

static boolean isValidWord(String word)

in PredictivePrototype, which checks if a given word is valid.

Words in the dictionary with upper case letters should be converted to lower-case because only lower-case letters should be returned by the signatureToWords method.

You should be able to complete this part of the Worksheet and test it in about one lab session.

To create the command-line programs, you will need to use the args array of the method:

public static void main(String[] args)

which contains the command line input. For example, when executing

java predictive.Words2SigProto Hello World! this is the input

the args array will contain

[“Hello”, “World!”, “this”, “is”, “the”, “input”]

You should ignore any words with non-alphabetic characters given in the input of

Sigs2WordsProto.

Format the output of Sigs2WordsProto as one line per signature, as there may be more than one word for a given numeric signature. E.g.

java predictive.Sigs2WordsProto 4663 329

4663 : good gone home hone hood hoof

329 : dax fax faz day fay daz

the actual output you get will depend on the dictionary used.

Notice that the package name predictive qualifies the class name, and this command works in the main directory.

The program Words2SigProto can be tested by converting large amounts of text to signatures, the output can be used to test Sigs2WordsProto (and later, in timing comparisons). Try using news articles to start with.

### 2 Storing and Searching a Dictionary(25%)

In the remaining parts of the worksheet, you are asked to implement a number of dictionary classes that will be more efficient than the prototype. All of these classes should implement this interface:

public interface Dictionary{

public Set<String> signatureToWords(String signature);

}

The required method signatureToWords finds the possible words that could correspond to a given signature and returns them as a set.

In this part, you will read and store the dictionary in memory as a list of pairs. As the list will be sorted and in memory, a faster look-up technique can be used.

1. (15%) : Create a class named ListDictionary.

Write a constructor for the class ListDictionary that takes a String path to the dictionary, reads and stores it in an ArrayList. Each entry of the ArrayList must be a pair, consisting of the word that has been read in and its signature. For this purpose, you will need to create a class named WordSig that pairs words and signatures (see the hints).

The wordToSignature method will be the same so you can re-use the code from the first part.

The signatureToWords method must be re-written as an instance method in the ListDictionary class to use the stored dictionary. The ArrayList<WordSig> must be stored in sorted order and the signatureToWords method must use binary search to perform the look-ups.

2. (10%) : Design and create a command-line program Sigs2WordsList for testing the ListDictionary class.

Compare the time taken to complete the execution of Sigs2WordsList and Sigs2- WordsProto with the same large input(s). Is it possible to make the time difference between Sigs2WordsList and Sigs2WordsProto noticeable? Make a note of the data you use and your timing results.

Hints :

Create a class which pairs the numeric signatures with words, like this:

When you read the dictionary you will need to create new WordSig objects.

A list of Comparable objects can be sorted using the method Collections.sort1.

To automatically sort a list using the collections API, the objects WordSig stored in the list must implement the Comparable interface. That means they must have a compareTo(…) method. compareTo returns -1, 0 or 1 according to whether the current object is less than, equal to, or greater than the argument object, in  the intended ordering.

Sort the dictionary only once.

You must decide how to define the compareTo method so as to allow efficient search for signatures. Even though, normally, you  are expected to redefine the equals method to be consistent with compareTo, for this version of the program, you can ignore this requirement. That is, you should not attempt to define an equals method.

You can search a sorted list using Collections.binarySearch. Its simplified type can be written as follows:

static <T> int binarySearch(List<T>, T)

Note that the type variable T in both the arguments must be the same.

Binary search will return the index of the first match it finds.  You must return all

matching words.  Scan above and below the found index to collect all matching words.

There are many ways of timing your application. One possible solution is given at the following link: https://bit.ly/2Stn3qk

### 3 More Efficiency (25%)

This part involves  creating an improved implementation of the Dictionary interface using   a Map data structure.

1. (20%) : Implement a new class MapDictionary.

Write a constructor for the class MapDictionary that takes a String path to the dictionary and stores the dictionary in a multi-valued Map. In this context, a “multi- valued map” is a data structure that maps each signature to set of words. Using a Map, data can be retrieved quickly by looking up a signature as in ListDictionary, but now it does not require scanning either side of the index as earlier. MapDictionary will also allow efficient insertion of new words in the dictionary while still allowing fast look-up.

You must choose a Map implementation from the Java Collections API. Explain how the map works and justify your choice in a comment.

Write a method signatureToWords that returns, in a Set<String>, only the matching whole words for the given signature. The character length of each returned word must be the same as the input signature.

2. (5%) : Create a program Sigs2WordsMap that uses the MapDictionary class. It should be possible to modify just one line in your Sigs2WordsList program so that it can work with any given implementation of the Dictionary interface.

Hints:

The MapDictionary class must implement Dictionary. Do not use the WordSig class.

When deciding what your Map will store in MapDictionary, keep in mind that one signature often corresponds to several words.

• When developing ListDictionary, you may have noticed that it was useful to create helper methods to add words to the data structure. Creating add helpers will simplify the constructors of both MapDictionary and TreeDictionary.

### 4 Prefix-matching (25%)

This part involves creating another improved implementation of the Dictionary interface using your own tree data structure. This should allow the words or parts of words that match partial signatures, so that the users will be able to see the parts of the words they are typing as they type.

1. (20%) : Implement a new class TreeDictionary that now stores the dictionary in your own tree implementation. It should support efficient search as well as efficient insertion of new words. In addition, TreeDictionary should support finding words when only some initial part of the signature (a prefix ) is known. This is so that the user can see the part of the word they intend to type as they are typing.

The TreeDictionary class forms a recursive data structure, similar to, but more general than binary trees taught in this semester. This tree differs in that each node now has up to eight branches, one for each number (2-9) that is allowed in a signature. Each path of the tree (from the root to a node) represents a signature or part of a signature. At each node of the tree, you must store a collection of all the words that can possibly match the partial signature along the path. That means that every word that has a prefix corresponding to the partial signature appears in the collection. For example, if the dictionary has the words a, ant and any, then the words at nodes corresponding to paths would be as follows:

at node 2, we have a, ant and any,

at node 2, 6, we have ant and any.

at node 2, 6, 8, we have only ant.

Write a constructor for the class TreeDictionary that takes a String path to the dictionary and populates the tree with words.

Write a method signatureToWords that returns, in a Set<String>, the matching words (and prefixes of words) for the given signature. The character length of each of the returned words or prefixes must be the same as the input signature.

2. (5%) : Create a program Sigs2WordsTree, similar to Sigs2WordsMap, that uses the TreeDictionary class.

Compare the time taken to complete the execution of Sigs2WordsMap and Sigs2WordsTree with large inputs. Is it possible  to  make  the  time  difference  between  Sigs2WordsList and Sigs2WordsMap or Sigs2WordsTree and Sigs2WordsMap noticeable? Again, make a note of the data you use and your timing results.

Hints:

The TreeDictionary class must implement Dictionary. Do not use the WordSig class.

Before starting TreeDictionary, sketch a tree-dictionary containing 2-3 words.

Every node of TreeDictionary will have a collection of words and eight TreeDictionarys. You may use an array of TreeDictionary or just store several objects, as you prefer.

The root node of TreeDictionary should not store any words.

In TreeDictionary it is more memory efficient to store only whole words as read-in from the dictionary. You should do this and write a helper-method to trim all the words in a given list to produce the output of signatureToWords.