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Lecture 10

Lecture 10. Introduction to Code Generation and Intermediate Representations. Introduction to Code Generation. Front end: Lexical Analysis Syntactic Analysis Intermediate Code Generation Back end: Intermediate Code Optimization Object Code Generation

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Lecture 10

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  1. Lecture 10 Introduction to Code Generation and Intermediate Representations Joey Paquet, 2000-2014

  2. 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 Joey Paquet, 2000-2014

  3. 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 Joey Paquet, 2000-2014

  4. Lexical Analyzer Syntactic Analyzer Intermediate Representation Intermediate Code Front End Back End Introduction to Code Generation Object Code Lexical Analyzer Syntactic Analyzer Intermediate Code Object Code Object Code Lexical Analyzer Syntactic Analyzer Intermediate Representation Lexical Analyzer Syntactic Analyzer Object Code Joey Paquet, 2000-2014

  5. 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. Joey Paquet, 2000-2014

  6. Part I Intermediate Representations Joey Paquet, 2000-2014

  7. 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. Abstract Syntax Trees Joey Paquet, 2000-2014

  8. x = a*b+a*b x = a*b+a*b Abstract Syntax Tree A = x = E x + + E E * * a b a b * * a b a b Parse vs Abstract Syntax Trees Parse Tree Joey Paquet, 2000-2014

  9. 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 implement lots of code optimization by avoiding redundant operations. Joey Paquet, 2000-2014

  10. Abstract Syntax Tree x = a*b+a*b x = a*b+a*b Directed Acyclic Graph = = x + x + * * * a b a b a b AST vs DAG Joey Paquet, 2000-2014

  11. 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  xab*ab*+= 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 Joey Paquet, 2000-2014

  12. 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 Joey Paquet, 2000-2014

  13. Three-Address Code • Three-address codes (3AC) is an intermediate language that maps directly to “assembly pseudo-code”, i.e. architecture-dependent assembly code • It breaks the program into short statements requiring no more than three variables and no more than one operator, e.g: source 3AC x = a+b*c t := b*c x := a+t Joey Paquet, 2000-2014

  14. 3AC ASM 3AC Quadruples t := b*c L 3,b M 3,c ST 3,t x := a+t L 3,a A 3,t ST 3,x t := b*c MULT t,b,c x := a+t ADD x,a,t 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 (or alias) is also stored in the symbol table • 3AC can also be represented as quadruples, which are even more related to assembly languages Joey Paquet, 2000-2014

  15. 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. Joey Paquet, 2000-2014

  16. Syntactic Analyzer Lexical Analyzer Moon Code Moon Interpreter Object Code Token Stream Source Code Project Overview • Your compiler generates Moon code • The Moon interpreter (virtual machine) is used to execute your output program • Your compiler is thus retargetable by recompilation of the moon compiler on your target processor Joey Paquet, 2000-2014

  17. Part II Semantic Actions and Code Generation Joey Paquet, 2000-2014

  18. Semantic Actions • Semantics is about giving a meaning to the compiled program. • Semantic actions have two parts: • Semantic checking: check if the compiled program can have a meaning, e.g variables are declared, operators and functions 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 Joey Paquet, 2000-2014

  19. 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 semantic action placeholders pushed on the stack along with the right hand sides they belong to. When a placeholder is removed from the stack, its corresponding semantic action is executed. • 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. Joey Paquet, 2000-2014

  20. Semantic Actions • There are semantic actions associated with: • Declarations: • variable declarations • type declarations • function declarations • Control structures: • conditional statements • loop statements • function calls • Assignments and expressions: • assignment operations • arithmetic and logical expressions Joey Paquet, 2000-2014

  21. 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 in the same scope. • This restriction is tested using the symbol table mechanism. • Symbol table entries are generated as declarations are encountered. • A symbol table is created every time a scope is entered. • Afterwards, every time an identifier is encountered, a check is made in the symbol table to ensure that it has been properly defined in the scope where the identifier is encountered. Joey Paquet, 2000-2014

  22. Processing Declarations • Code generation in type declarations comes in the form of calculation of the total memory size to be allocated 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, the data encoding used, and the word length of the computer, which depends on the target machine. • For each variable identifier declared, you must generate a unique 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. Joey Paquet, 2000-2014

  23. Processing Variable Declarations • <varDecl>  <type><id>; {varDeclSem} • An entry is created in the corresponding symbol table. If successful, memory space is reserved for the variable according to the size of the type of the variable and linked to a unique 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 offsets (size of the elements) are often stored in the symbol table record, though it can be calculated from the array’s type. • <varDecl>  <type><idList>; {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. Joey Paquet, 2000-2014

  24. Processing Type Declarations • Most programming languages allow the definition of types that are 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. • <typeDecl>  type <id> is <typeDef>; {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, to compute the offset when arrays of elements of that type are created, and when the members of a class are referred to in expressions. Joey Paquet, 2000-2014

  25. Processing Arrays • Static arrays are arrays with static size defined at compile time. • Most programming languages allow only integer literals for the initialization of array size, or constant integer variables when available in the language. • Pascal: A: array (1..10) of integer • C: int A[10]; or const size=10; int A[size]; Joey Paquet, 2000-2014

  26. 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 a static 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 elements) is also sometimes stored in the symbol table to facilitate code generation of array indexing during code generation. • Dynamic arrays are generally implemented using pointers, dynamic memory allocation functions and an execution stack or heap, which requires the implementation of a runtime system to execute the programs. Joey Paquet, 2000-2014

  27. 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 leaves 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. Joey Paquet, 2000-2014

  28. Processing Expressions • As new nodes (or subtrees) are created during tree creation/traversal, 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. • An entry is put in the symbol table for each intermediate result generated. It can then be used for further reference when doing semantic verification and translation while going upwards in the tree. Joey Paquet, 2000-2014

  29. = subtree ASM x + t1 = b*c L 3,b M 3,c ST 3,t1 t2 = a+t1 L 3,a A 3,t1 ST 3,t2 x = t2 L 3,t2 ST 3,x a * b c Processing Expressions • Doing so, the code is generated sequentially as the tree is traversed: Joey Paquet, 2000-2014

  30. 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. Joey Paquet, 2000-2014

  31. 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 translation phase. • Semantic translation is conditional to semantic checking. Joey Paquet, 2000-2014

  32. Conclusions • There are semantic actions for: • Declarations (variables, functions, types, etc) • Expressions (arithmetic, logic, etc) • Control structures (loops, conditions, function calls, etc) Joey Paquet, 2000-2014

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