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CSE 143 Lecture 14

CSE 143 Lecture 14. Maps Grammars Based on slides by Marty Stepp & Alyssa Harding. Example: studentGrades. (Reminder – Our Midterm is Monday Nov 9 th) We want to write a very simple program to keep track of each student’s grade on the midterm.

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CSE 143 Lecture 14

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  1. CSE 143Lecture 14 Maps Grammars Based on slides by Marty Stepp & Alyssa Harding

  2. Example: studentGrades (Reminder – Our Midterm is Monday Nov 9th) We want to write a very simple program to keep track of each student’s grade on the midterm. In other words, to associate a numeric grade with the name of each person in the class: Joe  32 Sally  87 Mike  51

  3. Example: studentGrades We could keep another list of all the grades Student at index 0 has grade at index 0, and so on But that is tedious... 0 1 2 students Joe Sally Mike grades 32 87 51

  4. Maps Solution: maps allow us to associate key/value pairs For example, a student name with a grade Also known as a dictionary, associative array, hash Can think of it as an array where you can have indexes of any type of Object instead of just ints student names grades Steve 32 Sally 51 Joe 87 Mike

  5. Maps Java’s Map<K,V>interface that uses generic key/value types // adds a mapping from the given key to the given value void put(K key, V value) // returns the value mapped to the given key (null if none) V get(K key) // returns true if map contains a mapping for the given key boolean containsKey(K key) // returns a Set of all keys in the map Set<K> keySet() // removes any existing mapping for the given key remove(K key)

  6. Maps We will use two implementations of the Mapinterface: TreeMap: provides O(log(n)) access to elements stores keys in sorted order HashMap: provides O(1) access to elements stores keys in unpredictable order The SortedMap interface is also implemented by TreeMap

  7. Example: studentGrades Using this, can solve our problem of grading by making a map: Map<String, Integer> studentGrades = new HashMap<String, Integer>(); And storing the grades in it: Random r = new Random(); for (String name : students) { int grade = r.nextInt(100); studentGrades.put(name, grade); }

  8. Example: studentGrades How can we see the grades? We can get a Set of all the keys we don’t know anything about a Set but it’s Iterable so we can use a foreach loop for (String name : studentGrades.keySet() ) { System.out.println(name+" "+ studentGrades.get(name)); }

  9. Example: wordCount • Let’s try a tougher problem now • Given some text file, we want to count how many times each word occurs // open the file Scanner console = new Scanner(System.in); System.out.print("What is the name of the text file? "); String fileName = console.nextLine(); Scanner input = new Scanner(new File(fileName));

  10. Example: wordCount • Make a SortedMap to hold the words and their counts: SortedMap<String, Integer> wordCounts = new TreeMap<String, Integer>();

  11. Example: wordCount • Put the words into the map: SortedMap<String, Integer> wordCounts = new TreeMap<String, Integer>(); while (input.hasNext()) { String next = input.next().toLowerCase(); wordCounts.put(next, 1); }

  12. Example: wordCount Put the words into the map: SortedMap<String, Integer> wordCounts = new TreeMap<String, Integer>(); while (input.hasNext()) { String next = input.next().toLowerCase(); wordCounts.put(next, 1); } But what if the word is already in the map? This would always keep its count at 1.

  13. Example: wordCount • Instead, we test whether it was there, and if so, increment it: while (input.hasNext()) { String next = input.next().toLowerCase(); if (!wordCounts.containsKey(next)) { wordCounts.put(next, 1); } else { wordCounts.put(next, wordCounts.get(next) + 1); } } Note that each key can only map to one value. When we put a key in multiple times, only the last value is recorded

  14. Example: wordCount • We can also print out all the word counts: for (String word : wordCounts.keySet()) { int count = wordCounts.get(word); System.out.println(count + "\t" + word); } Note that the keys (the words) occur in sorted order because we are using a SortedMap.

  15. Grammars

  16. Languages and grammars • (formal) language: A set of words or symbols. • grammar: A description of a language that describes which sequences of symbols are allowed in that language. • describes language syntax (rules) but not semantics (meaning) • can be used to generate strings from a language, or to determine whether a given string belongs to a given language

  17. Backus-Naur (BNF) • Backus-Naur Form (BNF): A syntax for describing language grammars in terms of transformation rules, of the form: <symbol> ::= <expression> | <expression> ...| <expression> • terminal: A fundamental symbol of the language. • non-terminal: A high-level symbol describing language syntax, which can be transformed into other non-terminal or terminal symbol(s) based on the rules of the grammar. • developed by two Turing-award-winning computer scientists in 1960 to describe their new ALGOL programming language

  18. An example BNF grammar <s> ::= <n> <v> <n> ::= Ruth | Morgan | Jordan | Alyssa <v> ::= cried | slept | belched • Nonterminals: • <s>, <n>, <v> • will not appear in an actual English sentence • can be transformed into one or more nonterminals or terminals • Terminals: • “Ruth”, “Alyssa”, and “slept” • they can appear in sentences • they only appear on the right side of rules

  19. An example BNF grammar <s> ::= <n> <v> <n> ::= Ruth | Morgan | Jordan | Alyssa <v> ::= cried | slept | belched • Some sentences that could be generated from this grammar: Alyssa slept Morgan belched Ruth cried

  20. BNF grammar version 2 <s> ::= <np> <v> <np> ::= <pn> | <dp> <n> <pn> ::= Ruth | Morgan | Jordan | Alyssa <dp> ::= a | the <n> ::= ball | hamster | carrot | computer <v> ::= cried | slept | belched • Some sentences that could be generated from this grammar: the carrot cried Ruth belched a computer slept

  21. BNF grammar version 3 <s> ::= <np> <v> <np> ::= <pn> | <dp> <adj> <n> <pn> ::= Ruth | Morgan | Jordan | Alyssa <dp> ::= a | the <adj> ::= silly | invisible | loud | romantic <n> ::= ball | hamster | carrot | computer <v> ::= cried | slept | belched • Some sentences that could be generated from this grammar: the invisible carrot cried Alyssa cried a computer slept a romantic ball belched

  22. Grammars & Recursion We could just make an <adj> rule: <adj>: silly | invisible | loud | romantic But we want to allow multiple adjectives: <adjp>:<adj>|<adj> <adj>|<adj> <adj> <adj>…??? OR we can use recursion to generate any number of adjectives: <adjp>:<adj>|<adj> <adjp>

  23. Grammars and recursion <s> ::= <np> <v> <np> ::= <pn> | <dp> <adjp> <n> <pn> ::= Ruth | Morgan | Jordan | Alyssa <dp> ::= a | the <adjp> ::= <adj> | <adj> <adjp> <adj> ::= silly | invisible | loud | romantic <n> ::= ball | hamster | carrot | computer <v> ::= cried | slept | belched • Grammar rules can be defined recursively, so that the expansion of a symbol can contain that same symbol. • There must also be expressions that expand the symbol into something non-recursive, so that the recursion eventually ends.

  24. Grammar, final version <s>::=<np> <vp> <np>::=<dp> <adjp> <n>|<pn> <dp>::=the|a <adjp>::=<adj>|<adj> <adjp> <adj>::=big|fat|green|wonderful|faulty|subliminal <n>::=dog|cat|man|university|father|mother|child <pn>::=John|Jane|Sally|Spot|Fred|Elmo <vp>::=<tv> <np>|<iv> <tv>::=hit|honored|kissed|helped <iv>::=died|collapsed|laughed|wept • Could this grammar generate the following sentences? Fred honored the green wonderful child big Jane wept the fat man fat • Generate a random sentence using this grammar.

  25. Sentence generation <s> <np> <vp> <tv> <np> <pn> <dp> <adjp> <n> <adj> <adjp> <adj> Fred honored the green wonderful child

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