Compiler principles, PS1
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1 Compiler principles, PS1 1 Compiler structure A compiler is a computer program that transforms source code written in a programming language into another computer language. Structure of a compiler: Scanner Parser Semantic analyzer Code generation Scanner (lexical analysis) converts a sequence of characters into a sequence of tokens. Parser (syntactic analysis) checks for correct syntax and builds a hierarchical structure (parse tree) implicit in the input tokens. Semantic analyzer (semantic analysis) compiler adds semantic information to the parse tree and builds the symbol table. This phase performs semantic checks such as type checking, object binding etc. Code generation process of converting some intermediate representation of the source code into another computer language. Python Python is a widely used general-purpose, high-level programming language. Its design philosophy emphasizes code readability, and its syntax allows programmers to express concepts in fewer lines of code. Python supports multiple programming paradigms, including object-oriented, imperative and functional programming or procedural styles. It features a dynamic type system and automatic memory management. In the course we will use Python 3.3. that can be downloaded from here. 1
2 .1 Variables Variables are nothing but reserved memory locations to store values. Python variables do not have to be explicitly declared to reserve memory space. The declaration happens automatically when you assign a value to a variable. 1 counter = 0 # An i n t e g e r assignment miles = # A f l o a t i n g p o i n t 3 name = " H e l l o " # A s t r i n g 4 5 a = b = c = 1 # M u l t i p l e Assignment 6 a, b, c = 1,, " john " # Assign m u l t i p l e o b j e c t s to m u l t i p l e v a r i a b l e s. Lists A list contains items separated by commas and enclosed within square brackets. The values stored in a list can be accessed using the slice operator ( [] and [:] ) with indexes starting at 0 in the beginning of the list and working their way to end -1. The plus ( + ) sign is the list concatenation operator. 1 list = [ " abcd ", 13,. 3 ] 3 p r i n t ( list ) # P r i n t s complete l i s t 4 p r i n t ( list [ 0 ] ) # P r i n t s f i r s t element o f the l i s t 5 p r i n t ( list [ 1 : 3 ] ) # P r i n t s elements s t a r t i n g from nd t i l l 3 rd 6 p r i n t ( list [ : ] ) # P r i n t s elements s t a r t i n g from 3 rd element 7 p r i n t ( list ) # P r i n t s l i s t two times 8 p r i n t ( list + [ 1, " a " ] ) # P r i n t s concatenated l i s t s.3 Functions The keyword def introduces a function definition. It must be followed by the function name and the parenthesized list of formal parameters. The statements that form the body of the function start at the next line, indented by a tab stop. 1 d e f fib ( n ) : # w r i t e F i b o n a c c i s e r i e s up to n " P r i n t a F i b o n a c c i s e r i e s up to n " 3 a, b = 0, 1 4 w h i l e b < n : 5 p r i n t ( b ) 6 a, b = b, a+b 7 8 fib ( 1 0 ) 9 11 f = lambda x : x + # anonymous f u n c t i o n 1 13 f ( 5 ).4 Classes Python classes provide all the standard features of Object Oriented Programming: the class inheritance mechanism allows multiple base classes, a derived
3 class can override any methods of its base class or classes, and a method can call the method of a base class with the same name. In C++ terminology, normally class members (including the data members) are public (except see below Private Variables and Class-local References), and all member functions are virtual. 1 c l a s s MyClass : #A simple c l a s s i = d e f init ( self, realpart, imagpart= 1) : 5 self. r = realpart 6 self. i = imagpart 7 8 d e f f ( self ) : 9 r e t u r n " f o o " 11 c l a s s DerivedClass ( MyClass ) : 1 13 d e f init ( self, realpart = 1) : 14 MyClass ( self, realpart ) d e f f ( self ) : 17 r e t u r n " goo " o1 = MyClass ( 0 ) 1 o = DerivedClass ( ) 3 o1. i 4 o. f ( ) 3 Parse combinators In functional programming, a parser combinator is a higher-order function which accepts several parsers as input and returns a new parser as its output. In this context, a parser is a function accepting strings as input and returning some structure as output. Parser combinators enable a recursive descent parsing strategy which facilitates modular piecewise construction and testing. This parsing technique is called combinatory parsing. Parsers built using combinators are straightforward to construct, readable, modular, well-structured and easily maintainable. The Parsing combinators in Python can be found here. The basic parsing classes are: const - represents a constant matcher epsilon - represents an empty input matcher caten - parser that matches concatenation of results of two given parsers disj - parser that matches disjunction of results of two given parsers star - parser that matches zero or more repetitions of result of a given parser
4 butnot - parser that matches result of first parser but not the result of second one Consider following grammar: < F raction >::=< Int > / < Int > < Int >::=< Nat > < Nat > < Nat >::= D 1 D 0 D 1 ::= D 0 ::= 0 D 1 One can implement parser recognizing the language of given grammar using parsing combinators following way: 1 D1 = const ( lambda x : x >= " 0 " and x <= " 9 " ) 3 D0 = disj ( const ( lambda x : x == " 0 " ), D1 ) 4 5 Nat = caten ( D1, star ( D0 ) ) 6 7 Int = disj ( Nat, caten ( const ( lambda x : x == " " ), Nat ) ) 8 9 Fract = caten ( Int, caten ( const ( lambda x : x == " / " ), Int ) ) Or by using Parser stack: 1 ps = ParserStack ( ) 3 ps. const ( lambda x : x >= " 0 " and x <= " 9 " ) 4 D1 = ps. done ( ) 5 6 ps. parser ( D1 ) 7 ps. const ( lambda x : x == " 0 " ) 8 ps. disj ( ) 9 D0 = ps. done ( ) 11 ps. parser ( D1 ) 1 ps. parser ( D0 ) 13 ps. star ( ) 14 ps. caten ( ) 15 Nat = ps. done ( ) ps. const ( lambda x : x == " " ) 18 ps. parser ( Nat ) 19 ps. caten ( ) 0 ps. parser ( Nat ) 1 ps. disj ( ) Int = ps. done ( ) 3 4 ps. parser ( Int ) 5 ps. const ( lambda x : x == " / " ) 6 ps. caten ( ) 7 ps. parser ( Int ) 8 ps. caten ( ) 9 Fract = ps. done ( )
5 3.1 Left recursion Immediate left recursion occurs in rules of the form A Aα β where α and β are sequences of nonterminals and terminals, and β doesn t start with A. Indirect left recursion in its simplest form could be defined as: A Bα C B Aβ D possibly giving the derivation A Bα Aβα... Example: Expr Expr + T erm T erm T erm T erm F actor F actor F actor (Expr) Int After removing left-recursion, we have the following grammar: Expr T ermexpr Expr +T ermexpr ɛ T erm F actort erm T erm F actort erm ɛ F actor (Expr) Int
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