Assignment
1. Purpose
The purpose of this assignment is to implement sorting algorithms for the autocomplete application.
2. Description
Write a program to implement autocomplete for a given set of N terms, where a term is a query string and an associated nonnegative weight. That is, given a prefix, find all queries that start with the given prefix, in descending order of weight.
Autocomplete is pervasive in modern applications. As the user types, the program predicts the complete query (typically a word or phrase) that the user intends to type. Autocomplete is most effective when there are a limited number of likely queries. For example, the Internet Movie Database uses it to display the names of movies as the user types; search engines use it to display suggestions as the user enters web search queries; cell phones use it to speed up text input.
In these examples, the application predicts how likely it is that the user is typing each query and presents to the user a list of the top-matching queries, in descending order of weight. These weights are determined by historical data, such as box office revenue for movies, frequencies of search queries from other Google users, or the typing history of a cell phone user. For the purposes of this assignment, you will have access to a set of all possible queries and associated weights (and these queries and weights will not change).
The performance of autocomplete functionality is critical in many systems. For example, consider a search engine which runs an autocomplete application on a server farm. According to one study, the application has only about 50ms to return a list of suggestions for it to be useful to the user. Moreover, in principle, it must perform this computation for every keystroke typed into the search bar and for every user!
In this assignment, you will implement autocomplete by sorting the terms by query string (with running time O(N log N) in sorting, or even better, where N is the of terms); binary searching to find all query strings that start with a given prefix (with running time O(log N)); and sorting the matching terms by weight (with running time O(M log M) in sorting, where M is the number of matching terms). Finally display results for the user. The following shows the top seven queries (city names) that start with AI M with weights equal to their populations.
Part 1: Autocomplete Term
Write an immutable data type Term.java that represents an autocomplete term: a query string and an associated integer weight. You must implement the following API, which supports comparing terms by three different orders: lexicographic order by query string (the natural order); in descending order by weight (an alternate order); and lexicographic order by query string but using only the first r characters (a family of alternate orderings). The last order may seem a bit odd, but you will use it in Part
3 to find all query strings that start with a given prefix (of length r).
Part 2: Binary Search
When binary searching a sorted array that contains more than one key equal to the search key, the client may want to know the index of either the first or the last such key. Accordingly, implement the following API:
Corner cases. Each static method should throw a java.lang.NullPointerException if any of its arguments is null. You should assume that the argument array is in sorted order (with respect to the supplied comparator).
Performance requirements. The firstIndexOf() and lastIndexOf() methods should make at most 1 + ⌈log2 N⌉ compares in the worst case, where N is the length of the array. In this context, a compare is one call to comparator.compare().
Part 3: Autocomplete
In this part, you will implement a data type that provides autocomplete functionality for a given set of string and weights, using Term and BinarySearchDeluxe. To do so, sort the terms in lexicographic order; use binary search to find the all query strings that start with a given prefix; and sort the matching terms in descending order by weight. Organize your program by creating an data type Autocomplete with the following API:
Corner cases. The constructor should throw a java.lang.NullPointerException if its argument is null or if any of the entries in its argument array are null. Each method should throw a java.lang.NullPointerException if its argument is null.
Performance requirements. The constructor should make proportional to N log N compares (or better) in the worst case, where N is the number of terms. The allMatches() method should make proportional to log N + M log M compares (or better) in the worst case, where M is the number of matching terms. In this context, a compare is one call to any of the compare()or compareTo() methods defined in Term.
Input format for testing
We provide a number of sample input files for testing. Each file consists of an integer N followed by N pairs of query strings and nonnegative weights. There is one pair per line, with the weight and string separated by a tab. A weight can be any integer between 0 and 2^63 - 1. A query string can be an arbitrary sequence of Unicode characters, including spaces (but not newlines).
• The file wiktionary.txt contains the 10,000 most common words in Project Gutenberg, with weights proportional to their frequencies.
• The file cities.txt contains over 90,000 cities, with weights equal to their populations.
Attachment:- Attachments.rar