Presentation is loading. Please wait.

Presentation is loading. Please wait.

Joey Paquet, 2000, 20021 Lecture 10 Introduction to Code Generation and Intermediate Representations.

Similar presentations


Presentation on theme: "Joey Paquet, 2000, 20021 Lecture 10 Introduction to Code Generation and Intermediate Representations."— Presentation transcript:

1 Joey Paquet, 2000, 20021 Lecture 10 Introduction to Code Generation and Intermediate Representations

2 Joey Paquet, 2000, 20022 Introduction to Code Generation Front end: –Lexical Analysis –Syntactic Analysis –Intermediate Code Generation Back end: –Intermediate Code Optimization –Object Code Generation The front end is machine-independent, i.e. it can be reused to build compilers for different architectures The back end is machine-dependent, i.e. these steps are related to the nature of the assembly or machine language of the target architecture

3 Joey Paquet, 2000, 20023 Introduction to Code Generation After syntactic analysis, we have a number of options to choose from: –generate object code directly from the parse –generate intermediate code, and then generate object code from it –generate an intermediate abstract representation, and then generate code directly from it –generate an intermediate abstract representation, generate intermediate code, and then the object code All these options have one thing in common: they are all based on syntactic information gathered in the semantic analysis

4 Joey Paquet, 2000, 20024 Introduction to Code Generation Syntactic Analyzer Object Code Syntactic Analyzer Intermediate Representation Object Code Lexical Analyzer Lexical Analyzer Lexical Analyzer Syntactic Analyzer Intermediate Representation Intermediate Code Object Code Syntactic Analyzer Intermediate Code Object Code Lexical Analyzer Front EndBack End

5 Joey Paquet, 2000, 20025 Interm. Representations & Code Intermediate representations synthetize the syntactic information gathered during the parse, generally in the form of a tree or directed graph. Intermediate representations enable high-level code optimization. Intermediate code is a low-level coded (text) representation of the program, directly translatable to object code. Intermediate code enables low-level, architecture-dependent optimizations.

6 Joey Paquet, 2000, 20026 Part I Intermediate Representations

7 Joey Paquet, 2000, 20027 Abstract Syntax Trees Each node represents the application of a rule in the grammar A subtree is created only after the complete parsing of a right hand side Pointers to subtrees are sent up and grafted as upper subtrees are completed Parse trees (concrete syntax trees) emphasize the grammatical structure of the program Abstract syntax trees emphasize the actual computations to be performed. They do not refer to the actual non-terminals defined in the grammar, hence their name.

8 Joey Paquet, 2000, 20028 Parse vs Abstract Syntax Trees x = a*b+a*b x + = ab*ab* E A E E Parse Tree x abab * = * + x = a*b+a*b Abstract Syntax Tree

9 Joey Paquet, 2000, 20029 Directed Acyclic Graphs (DAG) Directed acyclic graphs (DAG) are a relative of syntax trees: they are used to show the syntactic structure of valid programs in the form of a “tree”. In DAGs, the nodes for repeated variables and expressions are merged into a single node. DAGs are more complicated to build than syntax trees, but directly implements lots of code optimization by avoiding redundant operations.

10 Joey Paquet, 2000, 200210 AST vs DAG x abab * = * + x = a*b+a*b Abstract Syntax Tree x = ab * + x = a*b+a*b Directed Acyclic Graph

11 Joey Paquet, 2000, 200211 Postfix Notation Every expression is rewritten with its operators at the end, e.g.: Easy to generate from a bottom-up parse Can be generated from a syntax tree using postorder traversal a+b  ab+ a+b*c  abc*+ if A then B else C  ABC? If A then if B then C else D else E  ABCD?E? x=a*b+a*b ab*ab*+x=

12 Joey Paquet, 2000, 200212 Postfix Notation Its nature allows it to be naturally evaluated with the use of a stack Operands are pushed onto the stack; operators pop the right amount of operands from the stack, do the operation, then push the result back onto the stack. However, this notation is restricted to simple expressions such as in arithmetics where every rule conveys an operation It cannot be used for the expression of most programming languages constructs

13 Joey Paquet, 2000, 200213 Three-Address Code Three-address codes (3AC) is an intermediate language that maps directly to assembly code, but that is not architecture-dependent It breaks the program into short statements requiring no more than three variables and no more than one operator, e.g: x = a+b*ct := b*c x := a+t source3AC

14 Joey Paquet, 2000, 200214 Three-Address Code The temporary variables are generated at compile time and added to the symbol table In the generated code, the variables will refer to actual memory cells. Their address is also stored in the symbol table 3AC can also be represented as quadruples, which are even more related to assembly languages t := b*cL 3,b M 3,c ST 3,t x := a+tL 3,a A 3,t ST 3,x 3ACASM t := b*cMULT t,b,c x := a+tADD x,a,t 3ACQuadruples

15 Joey Paquet, 2000, 200215 Intermediate Languages In this case, we generate code in a language for which we already have a compiler or interpreter Such languages are generally very low-level and dedicated to the compiler construction task It provides the compiler writer with a “virtual machine” Various compilers can be built using the same virtual machine The virtual machine compiler can be compiled on different machines to provide a translator to various architectures. For the project, we have the moon compiler, which provides a virtual assembly language and a compiler.

16 Joey Paquet, 2000, 200216 Project Overview Syntactic Analyzer Lexical Analyzer Moon Code Token Stream Moon Compiler Object Code Source Code Your compiler generates Moon code The Moon compiler (virtual machine) is used to generate an exectuable for your program Your compiler is thus retargetable by recompilation of the moon compiler on a new processor

17 Joey Paquet, 2000, 200217 Part II Semantic Actions and Code Generation

18 Joey Paquet, 2000, 200218 Semantic Actions Semantics is about giving a meaning to the compiled program. Semantic actions have two parts: –Semantic checking: check if the compiled program has a meaning, e.g variables are declared, operator and function have the right parameter types and number of parameters upon calling –Semantic translation: translate declarations, statements and expressions to machine code Semantic translation is conditional to semantic checking

19 Joey Paquet, 2000, 200219 Semantic Actions Semantic actions are inserted in the grammar (thus transforming it in an attribute grammar) –In recursive descent parsers, they are represented by function calls imbedded in the parsing functions –In table-driven top-down parsers, they are represented by functions pushed on the stack along with the right hand sides they belong to Most semantic actions use attributes for their resolution: –In recursive descent parsers, they are migrated using reference parameter passing –In table-driven top-down parsers, they are migrated using a semantic stack

20 Joey Paquet, 2000, 200220 Semantic Actions There are semantic actions associated with: –Declarations: variable declarations type declarations function declarations –Control structures: conditional statements loop statements –Expressions: assignment operations arithmetic and logical expressions

21 Joey Paquet, 2000, 200221 Processing Declarations In processing declarations, the only semantic checking there is to do is to ensure that every object (e.g. variable, type, class, function, etc.) is declared once and only once This restriction is tested using the symbol table entries Symbol table entries are generated as declarations are encountered Afterwards, every time an identifier is encountered, a check is made in the symbol table to ensure that it has been properly defined

22 Joey Paquet, 2000, 200222 Processing Declarations Code generation in declarations comes in the form of memory allocation for the objects defined Every object defined, no matter its type, will eventually have to be stored in the computer’s memory Memory allocation must be done according to the size of the objects defined, which depends on the target machine For each identifier declared, you must generate a label that will be used to refer to that variable in the ASM code and store it in the location field of its entry in the symbol table See the Moon machine description documentation for more explanations specific to the project

23 Joey Paquet, 2000, 200223 Processing Variable Declarations  ; {varDeclSem} –An entry is created in the corresponding symbol table. Memory space is reserved for the variable according to the size of the type of the variable and linked to a label in the ASM code –The starting address (or its label) is stored in the symbol table entry of the variable. In the case of arrays, the offset of (size of the elements) is often stored in the symbol table record  ; {varDeclSem} –To generate each entry, (one for each element in the list), the compiler must keep track of the type of the declaration. This is an attribute that is migrated using a technique appropriate to the parsing method used

24 Joey Paquet, 2000, 200224 Processing Type Declarations Most programming languages allow the definition of types that aggregates of the basic types defined in the language There are typically arrays or record types, or even abstract data types (or classes) in object-oriented programming languages  is ; {typeDeclSem} –An entry is created in the symbol table for the new type defined. It contains a definition (e.g. size) of all the elements of the new type –This information is used when new objects of that type are declared in the program, and to compute the offset when arrays of elements of that type are created

25 Joey Paquet, 2000, 200225 Type Compatibility In Pascal: –A,B: array (1..10) of integer; –C,D: array (1..10) of integer; this defines two data types: –type Type1 is array (1..10) of integer; –A,B: Type1 –type Typ2 is array (1..10) of integer; –C,D: Type2 Here, Type1 and Type2 are clearly two distinct data types, e.g. A := D is not permitted in the program

26 Joey Paquet, 2000, 200226 Type Compatibility Some compilers use some rules to define type equivalence. One of the first compilers to implement this was the Algol68 compiler Advantage: –gives more flexibility to the language Drawbacks: –compiler is much more complicated to implement –compiler will hardly distinguish between equivalent types

27 Joey Paquet, 2000, 200227 Processing Arrays Static arrays are arrays with static size defined at compile time Most programming languages allow only integer litterals for the initialization of array size, or constant integer variables when available in the language Pascal: A: array (1..10) if integer C: int A[10]; or const size=10; int A[size];

28 Joey Paquet, 2000, 200228 Processing Arrays This restriction comes from the fact that the memory allocated to the array has to be set at compile time, and is fixed throughout the execution of the program When processing an array declaration, a sufficient amount of memory is allocated to the variable depending on the size of the elements and the cardinality of the array Only the starting address (or a label) is stored in the symbol table. The offset (the size of the array in memory) is also sometimes stored in the symbol table record to avoid referring of elements outside the bounds Dynamic arrays are generally implemented using pointers, dynamic memory allocation functions and an execution stack or heap

29 Joey Paquet, 2000, 200229 Processing Expressions Semantic records contain the type and location for variables (normally labels in the ASM code) or the type and value for constant factors Semantic records are created at the leafs of the tree when factors (F) are recognized, and then passed upwards in the tree These semantic records contain the attributes that are migrated within the tree to find a global result for the symbol on top of the tree for that expression

30 Joey Paquet, 2000, 200230 Processing Expressions As new nodes (or subtrees) are created going up in the tree, intermediate results are stored in temporary semantic records containing subresults for subexpressions Each time an operator node is resolved, its corresponding semantic checking and translation is done and its subresult is stored in a temporary variable for which you have to allocate some memory and generate a label You can even put an entry in the symbol table for each intermediate result you generated. You can then use these for further reference, e.g. for debugging

31 Joey Paquet, 2000, 200231 Processing Expressions Doing so, the code is generated sequentially as the tree is traversed: a bc + * x = t1 = b*cL 3,b M 3,c ST 3,t1 t2 = a+t1L 3,a A 3,t1 ST 3,t2 x = t2L 3,t2 ST 3,x subtreeASM

32 Joey Paquet, 2000, 200232 Conclusions Most compilers build an intermediate representation of the parsed program, normally as an abstract syntax tree. These will allow high-level optimizations to occur before the code is generated. In the project, we are outputting MOON code, which is an intermediate language. MOON code could be the subject of low- level optimizations.

33 Joey Paquet, 2000, 200233 Conclusions Semantic actions are composed of a semantic checking, and a semantic translation part. Semantic actions are inserted at appropriate places in the grammar to achieve the semantic checking and transaltion phase. Semantic translation is conditional to semantic checking.

34 Joey Paquet, 2000, 200234 Conclusions There are semantic actions for: –Declarations (variables, functions, types, etc) –Expressions (arithmetic, logic, etc) –Control structures (loops, conditions, etc)


Download ppt "Joey Paquet, 2000, 20021 Lecture 10 Introduction to Code Generation and Intermediate Representations."

Similar presentations


Ads by Google