1. LECTURE 36: DICTIONARY CSC 212 – Data Structures

2.  At simplest level, Map is collection of Entry s  These key-value pairs serve as the basic data in a Map  size() & isEmpty() methods analyzes Entry s  Searchable data stored using Map s  put() adds an Entry so key is mapped to the value  get() retrieves value associated with key from Map  remove() deletes the key & its value (an Entry )  At most one value per key using a Map What is a MAP?

3.  MAP great when you want only one value for a key  Credit card number goes to one account  One person has a given social security number  Only one definition for a word in the dictionary Where MAPS are Used

5.  May want to associate multiple values per key  key mapped to List of values is possible solution user  But this means MAP’s user must handle complexity Limitations of MAP

6. very  DICTIONARY ADT very similar to MAP  Searching through data is goal of each  Both are collections of Entry s  Associating keys with values using both concepts  DICTIONARY can map multiple values to one key  Like (real-world) dictionaries with definitions & words  Legal to associate only 1 value to a given key “awesome”  Also many Entry s with same key but different value “cool”“cool” Dictionary ADT

7. Changes for Dictionary MapDictionary V put(k,v)Entry insert(k,v) V remove(k)Entry remove(e) V get(k) Entry find(k) Iterable findAll(k)

8.  Simplest implementation uses unordered List  Question is: PositionList or IndexList  Consider the work we will be doing  find & findAll may scan through List  Check each Position to see if it contains a match  find method will stop at first matching key  Entire List scanned for matching keys in findAll Time needed for PositionList: Time needed for IndexList: Using an Unordered List

9.  May scan through List in call to remove  Check each element to see if it is a match  Stop when we find Entry and remove it  insert adds Entry to end of the List  Keys are not unique, so no checks are needed  Entry created for key-value pair is returned Time needed for PositionList: Time needed for IndexList: Unordered List Details

10.  Great when adds are common & frequent… …but searching & removing slower than molasses  When would we ever need this implementation? Unordered List

11.  Great when adds are common & frequent… …but searching & removing slower than molasses  When would we ever need this implementation?  Phone records  E-mail backups  Tax receipts by the IRS  Bank’s copy of your credit card orders Unordered List

12.  Could also use a hash table  Entry s definitely unordered within the table  We hope it provides O(1) time for most methods  find() & remove() unchanged from before  Others handle duplicate keys like a collision  Until null or AVAILABLE found check the indices  insert() will just keep trying the next index  More may exist that findAll() needs to find Hash Based Approach

13.  Start week #13 assignment  Due at usual time, whatever that may be  Work on programming project #4 (due 12/1)  2 nd Chance Midterm Thurs., 9:30 – 10:20 in WTC205  Finish section 9.3 of the book  How else could we implement a Dictionary?  What if we do not have a good hash supplier?  Are we doomed to poor performance? Before Next Lecture…