1. 1 Languages and Compilers (SProg og Oversættere) Lecture 2 Bent Thomsen Department of Computer Science Aalborg University With acknowledgement to Norm Hutchinson whose slides this lecture is based on.

2. 2 Today’s lecture Three topics –Treating Compilers and Interpreters as black-boxes Tombstone- or T- diagrams –A first look inside the black-box Your guided tour –Some Language Design Issues

3. 3 Terminology Translatorinputoutput source program object program is expressed in the source language is expressed in the implementation language is expressed in the target language Q: Which programming languages play a role in this picture? A: All of them!

4. 4 Tombstone Diagrams What are they? –diagrams consisting out of a set of “puzzle pieces” we can use to reason about language processors and programs –different kinds of pieces –combination rules (not all diagrams are “well formed”) M Machine implemented in hardware S -> T L Translator implemented in L MLML Language interpreter in L Program P implemented in L L P

5. 5 Tombstone diagrams: Combination rules S PP T S -> T M M L P M WRONG!OK! M M P M L P WRONG!

6. 6 Tetris x86C Tetris Compilation x86 Example: Compilation of C programs on an x86 machine C -> x86 x86 Tetris x86

7. 7 What is Tetris? Tetris® The World's Most Popular Video Game Since its commercial introduction in 1987, Tetris® has been established as the largest selling and most recognized global brand in the history of the interactive game software industry. Simple, entertaining, and yet challenging, Tetris® can be found on more than 60 platforms. Over 65 million Tetris® units have been sold worldwide to date.

8. 8 Tetris PPCC Tetris Cross compilation x86 Example: A C “cross compiler” from x86 to PPC C -> PPC x86 A cross compiler is a compiler which runs on one machine (the host machine) but emits code for another machine (the target machine). Host ≠ Target Q: Are cross compilers useful? Why would/could we use them? PPC Tetris PPC download

9. 9 Tetris x86 Tetris JVMJava Tetris Two Stage Compilation x86 Java->JVM x86 A two-stage translator is a composition of two translators. The output of the first translator is provided as input to the second translator. x86 JVM->x86 x86

10. 10 x86 Java->x86 Compiling a Compiler Observation: A compiler is a program! Therefore it can be provided as input to a language processor. Example: compiling a compiler. Java->x86 C x86 C -> x86 x86

11. 11 Interpreters An interpreter is a language processor implemented in software, i.e. as a program. Terminology: abstract (or virtual) machine versus real machine Example: The Java Virtual Machine JVM x86 JVM Tetris Q: Why are abstract machines useful?

12. 12 Interpreters Q: Why are abstract machines useful? 1) Abstract machines provide better platform independence JVM x86 PPC JVM Tetris JVM PPC JVM Tetris

13. 13 Interpreters Q: Why are abstract machines useful? 2) Abstract machines are useful for testing and debugging. Example: Testing the “Ultima” processor using hardware emulation Ultima x86 Ultima  P P Functional equivalence Note: we don’t have to implement Ultima emulator in x86 we can use a high-level language and compile it.

14. 14 Interpreters versus Compilers Q: What are the tradeoffs between compilation and interpretation? Compilers typically offer more advantages when –programs are deployed in a production setting –programs are “repetitive” –the instructions of the programming language are complex Interpreters typically are a better choice when –we are in a development/testing/debugging stage –programs are run once and then discarded –the instructions of the language are simple –the execution speed is overshadowed by other factors e.g. on a web server where communications costs are much higher than execution speed

15. 15 Interpretive Compilers Why? A tradeoff between fast(er) compilation and a reasonable runtime performance. How? Use an “intermediate language” more high-level than machine code => easier to compile to more low-level than source language => easy to implement as an interpreter Example: A “Java Development Kit” for machine M Java->JVM M JVM M

16. 16 P JVMJava P Interpretive Compilers Example: Here is how we use our “Java Development Kit” to run a Java program P Java->JVM M JVM M M JVM P M javac java

17. 17 Portable Compilers Example: Two different “Java Development Kits” Java->JVM JVM M Kit 2: Java->JVM M JVM M Kit 1: Q: Which one is “more portable”?

18. 18 Portable Compilers In the previous example we have seen that portability is not an “all or nothing” kind of deal. It is useful to talk about a “degree of portability” as the percentage of code that needs to be re-written when moving to a different machine. In practice 100% portability is as good as impossible.

19. 19 Example: a “portable” compiler kit Java->JVM Java JVM Java Java->JVM JVM Q: Suppose we want to run this kit on some machine M. How could we go about realizing that goal? (with the least amount of effort) Portable Compiler Kit:

20. 20 Example: a “portable” compiler kit Java->JVM Java JVM Java Java->JVM JVM Q: Suppose we want to run this kit on some machine M. How could we go about realizing that goal? (with the least amount of effort) JVM Java JVM C reimplement C->M M JVM M M

21. 21 Example: a “portable” compiler kit Java->JVM Java JVM Java Java->JVM JVM M This is what we have now: Now, how do we run our Tetris program? Tetris JVMJava Tetris M Java->JVM JVM M JVM Tetris JVM M M

22. 22 Bootstrapping Java->JVM Java JVM Java Java->JVM JVM Remember our “portable compiler kit”: We haven’t used this yet! Java->JVM Java Same language! Q: What can we do with a compiler written in itself? Is that useful at all? JVM M

23. 23 Bootstrapping Java->JVM Java Same language! Q: What can we do with a compiler written in itself? Is that useful at all? By implementing the compiler in (a subset of) its own language, we become less dependent on the target platform => more portable implementation. But… “chicken and egg problem”? How do to get around that? => BOOTSTRAPPING: requires some work to make the first “egg”. There are many possible variations on how to bootstrap a compiler written in its own language.

24. 24 Bootstrapping an Interpretive Compiler to Generate M code Java->JVM Java JVM Java Java->JVM JVM Our “portable compiler kit”: P M Java P Goal: we want to get a “completely native” Java compiler on machine M Java->M M JVM M M

25. 25 Bootstrapping an Interpretive Compiler to Generate M code (first approach) Step 1: implement Java->M JavaJVM Java ->M Java->JVM JVM M M Java ->M Java Step 2: compile it Step 3: Use this to compile again by rewriting Java ->JVM Java

26. 26 Bootstrapping an Interpretive Compiler to Generate M code (first approach) Step 3: “Self compile” the Java (in Java) compiler M Java->M JVM M M Java->M Java Java->M JVMThis is our desired compiler! Step 4: use this to compile the P program P M Java P Java->M M

27. 27 Bootstrapping an Interpretive Compiler to Generate M code (second approach) Idea: we will build a two-stage Java -> M compiler. P M P M Java P P JVM M Java->JVM M M JVM->M M We will make this by compiling To get this we implement JVM->M Java Java->JVM JVM and compile it

28. 28 Bootstrapping an Interpretive Compiler to Generate M code (second approach) Step 1: implement JVM->M JavaJVM JVM->M Java->JVM JVM M M JVM->M Java Step 2: compile it Step 3: compile this

29. 29 Bootstrapping an Interpretive Compiler to Generate M code (second approach) Step 3: “Self compile” the JVM (in JVM) compiler M JVM->M JVM M M JVM->M JVM JVM->M JVMThis is the second stage of our compiler! Step 4: use this to compile the Java compiler

30. 30 Bootstrapping an Interpretive Compiler to Generate M code Step 4: Compile the Java->JVM compiler into machine code M Java->JVM M JVM JVM->M MThe first stage of our compiler! We are DONE! P M P M Java P P JVM M Java->JVM M M JVM->M M

31. 31 Full Bootstrap A full bootstrap is necessary when we are building a new compiler from scratch. Example: We want to implement an Ada compiler for machine M. We don’t currently have access to any Ada compiler (not on M, nor on any other machine). Idea: Ada is very large, we will implement the compiler in a subset of Ada and bootstrap it from a subset-of-Ada compiler in another language. (e.g. C) Ada-S ->M C v1 Step 1: build a compiler for Ada-S in another language

32. 32 Full Bootstrap Ada-S ->M C v1 Step 1a: build a compiler (v1) for Ada-S in another language. Ada-S ->M C v1 M Ada-S->M v1 Step 1b: Compile v1 compiler on M M C->M M This compiler can be used for bootstrapping on machine M but we do not want to rely on it permanently!

33. 33 Full Bootstrap Ada-S ->M Ada-S v2 Step 2a: Implement v2 of Ada-S compiler in Ada-S Ada-S ->M Ada-S v2 M M Ada-S->M v2 Step 2b: Compile v2 compiler with v1 compiler Ada-S ->M M v1 Q: Is it hard to rewrite the compiler in Ada-S? We are now no longer dependent on the availability of a C compiler!

34. 34 Full Bootstrap Step 3a: Build a full Ada compiler in Ada-S Ada->M Ada-S v3 M M Ada->M v3 Ada-S ->M M v2 Step 3b: Compile with v2 compiler Ada->M Ada-S v3 From this point on we can maintain the compiler in Ada. Subsequent versions v4,v5,... of the compiler can be written in Ada and each compiled with the previous version.

35. 35 Half Bootstrap We discussed full bootstrap which is required when we have no access to a compiler for our language at all. Q: What if we have access to a compiler for our language on a different machine HM but want to develop one for TM ? Ada->HM HM We have: Ada->TM TM We want: Idea: We can use cross compilation from HM to TM to bootstrap the TM compiler. Ada->HM Ada

36. 36 HM Ada->TM Half Bootstrap Idea: We can use cross compilation from HM to M to bootstrap the M compiler. Step 1: Implement Ada->TM compiler in Ada Ada->TM Ada Step 2: Compile on HM Ada->TM Ada Ada->HM HM Cross compiler: running on HM but emits TM code

37. 37 TM Ada->TM Half Bootstrap Step 3: Cross compile our TM compiler. Ada->TM Ada Ada->TM HM DONE! From now on we can develop subsequent versions of the compiler completely on TM

38. 38 Bootstrapping to Improve Efficiency The efficiency of programs and compilers: Efficiency of programs: - memory usage - runtime Efficiency of compilers: - Efficiency of the compiler itself - Efficiency of the emitted code Idea: We start from a simple compiler (generating inefficient code) and develop more sophisticated versions of it. We can then use bootstrapping to improve performance of the compiler.

39. 39 Bootstrapping to Improve Efficiency We have: Ada->M slow Ada Ada-> M slow M slow We implement: Ada->M fast Ada Ada->M fast Ada M Ada->M fast M slow Step 1 Ada-> M slow M slow Step 2 Ada->M fast Ada M Ada->M fast M fast Ada-> M fast M slow Fast compiler that emits fast code!

40. 40 Conclusion To write a good compiler you may be writing several simpler ones first You have to think about the source language, the target language and the implementation language. Strategies for implementing a compiler 1.Write it in machine code 2.Write it in a lower level language and compile it using an existing compiler 3.Write it in the same language that it compiles and bootstrap The work of a compiler writer is never finished, there is always version 1.x and version 2.0 and …

41. 41 Compilation So far we have treated language processors (including compilers) as “black boxes” Now we take a first look "inside the box": how are compilers built. And we take a look at the different “phases” and their relationships

42. 42 The “Phases” of a Compiler Syntax Analysis Contextual Analysis Code Generation Source Program Abstract Syntax Tree Decorated Abstract Syntax Tree Object Code Error Reports

43. 43 Different Phases of a Compiler The different phases can be seen as different transformation steps to transform source code into object code. The different phases correspond roughly to the different parts of the language specification: Syntax analysis Syntax Contextual analysis Contextual constraints Code generation Semantics

44. 44 Mini Triangle Mini Triangle is a very simple Pascal-like programming language. An example program: !This is a comment. let const m ~ 7; var n in begin n := 2 * m * m ; putint(n) end !This is a comment. let const m ~ 7; var n in begin n := 2 * m * m ; putint(n) end Declarations Command Expression

45. 45 Syntax of Mini Triangle Program ::= single-Command single-Command ::= V-name := Expression | Identifier ( Expression ) | if Expression then single-Command else single-Command | while Expression do single-Command | let Declaration in single-Command | begin Command end Command ::= single-Command | Command ; single-Command Program ::= single-Command single-Command ::= V-name := Expression | Identifier ( Expression ) | if Expression then single-Command else single-Command | while Expression do single-Command | let Declaration in single-Command | begin Command end Command ::= single-Command | Command ; single-Command

46. 46 Syntax of Mini Triangle (continued) Expression ::= primary-Expression | Expression Operator primary-Expression primary-Expression ::= Integer-Literal | V-name | Operator primary-Expression | ( Expression ) V-name ::= Identifier Identifier ::= Letter | Identifier Letter | Identifier Digit Integer-Literal ::= Digit | Integer-Literal Digit Operator ::= + | - | * | / | | = Expression ::= primary-Expression | Expression Operator primary-Expression primary-Expression ::= Integer-Literal | V-name | Operator primary-Expression | ( Expression ) V-name ::= Identifier Identifier ::= Letter | Identifier Letter | Identifier Digit Integer-Literal ::= Digit | Integer-Literal Digit Operator ::= + | - | * | / | | =

47. 47 Syntax of Mini Triangle (continued) Declaration ::= single-Declaration | Declaration ; single-Declaration single-Declaration ::= const Identifier ~ Expression | var Identifier : Type-denoter Type-denoter ::= Identifier Declaration ::= single-Declaration | Declaration ; single-Declaration single-Declaration ::= const Identifier ~ Expression | var Identifier : Type-denoter Type-denoter ::= Identifier Comment ::= ! CommentLine eol CommentLine ::= Graphic CommentLine Graphic ::= any printable character or space Comment ::= ! CommentLine eol CommentLine ::= Graphic CommentLine Graphic ::= any printable character or space

48. 48 Syntax Trees A syntax tree is an ordered labeled tree such that: a) terminal nodes (leaf nodes) are labeled by terminal symbols b) non-terminal nodes (internal nodes) are labeled by non terminal symbols. c) each non-terminal node labeled by N has children X 1,X 2,...X n (in this order) such that N := X 1,X 2,...X n is a production.

49. 49 Syntax Trees Example: Expression V-name primary-Exp. Expression Ident d + primary-Exp OpInt-Lit 10* Op V-name primary-Exp. Ident d Expression ::= Expression Op primary-Exp 123 1 2 3

50. 50 Concrete and Abstract Syntax The previous grammar specified the concrete syntax of Mini Triangle. The concrete syntax is important for the programmer who needs to know exactly how to write syntactically well- formed programs. The abstract syntax omits irrelevant syntactic details and only specifies the essential structure of programs. Example: different concrete syntaxes for an assignment v := e (set! v e) e -> v v = e

51. 51 Concrete Syntax of Commands single-Command ::= V-name := Expression | Identifier ( Expression ) | if Expression then single-Command else single-Command | while Expression do single-Command | let Declaration in single-Command | begin Command end Command ::= single-Command | Command ; single-Command single-Command ::= V-name := Expression | Identifier ( Expression ) | if Expression then single-Command else single-Command | while Expression do single-Command | let Declaration in single-Command | begin Command end Command ::= single-Command | Command ; single-Command

52. 52 Abstract Syntax of Commands Command ::= V-name := Expression AssignCmd | Identifier ( Expression ) CallCmd | if Expression then Command else Command IfCmd | while Expression do Command WhileCmd | let Declaration in Command LetCmd | Command ; Command SequentialCmd Command ::= V-name := Expression AssignCmd | Identifier ( Expression ) CallCmd | if Expression then Command else Command IfCmd | while Expression do Command WhileCmd | let Declaration in Command LetCmd | Command ; Command SequentialCmd

53. 53 Concrete Syntax of Expressions (recap) Expression ::= primary-Expression | Expression Operator primary-Expression primary-Expression ::= Integer-Literal | V-name | Operator primary-Expression | ( Expression ) V-name ::= Identifier Expression ::= primary-Expression | Expression Operator primary-Expression primary-Expression ::= Integer-Literal | V-name | Operator primary-Expression | ( Expression ) V-name ::= Identifier

54. 54 Abstract Syntax of Expressions Expression ::= Integer-Literal IntegerExp | V-name VnameExp | Operator Expression UnaryExp | Expression Op Expression BinaryExp V-name::= Identifier SimpleVName Expression ::= Integer-Literal IntegerExp | V-name VnameExp | Operator Expression UnaryExp | Expression Op Expression BinaryExp V-name::= Identifier SimpleVName

55. 55 Abstract Syntax Trees Abstract Syntax Tree for: d:=d+10*n BinaryExpression VNameExp BinaryExpression Ident d + Op Int-Lit 10 * Op SimpleVName IntegerExpVNameExp Ident n SimpleVName AssignmentCmd d Ident VName SimpleVName

56. 56 1) Syntax Analysis Syntax Analysis Source Program Abstract Syntax Tree Error Reports Note: Not all compilers construct an explicit representation of an AST. (e.g. on a “single pass compiler” generally no need to construct an AST) Note: Not all compilers construct an explicit representation of an AST. (e.g. on a “single pass compiler” generally no need to construct an AST)

57. 57 Example Program We now look at each of the three different phases in a little more detail. We look at each of the steps in transforming an example Mini Triangle program into TAM code. ! This program is useless except for ! illustration let var n: integer; var c: char in begin c := ‘&’; n := n+1 end

58. 58 1) Syntax Analysis -> AST Program LetCommand SequentialDeclaration n Integer c Char c ‘&’ n n + 1 Ident OpChar.LitInt.Lit SimpleT VarDecl SimpleT VarDecl SimpleV Char.Expr SimpleV VNameExpInt.Expr AssignCommandBinaryExpr SequentialCommand AssignCommand

59. 59 2) Contextual Analysis -> Decorated AST Contextual Analysis Decorated Abstract Syntax Tree Error Reports Abstract Syntax Tree Contextual analysis: Scope checking: verify that all applied occurrences of identifiers are declared Type checking: verify that all operations in the program are used according to their type rules. Annotate AST: Applied identifier occurrences => declaration Expressions => Type

60. 60 2) Contextual Analysis -> Decorated AST Program LetCommand SequentialDeclaration n Ident SimpleT VarDecl SimpleT VarDecl Integer c Charc‘&’ nn +1 Ident OpChar.LitInt.Lit SimpleV Char.Expr SimpleV VNameExpInt.Expr AssignCommandBinaryExpr SequentialCommand AssignCommand :char :int

61. 61 Contextual Analysis Finds scope and type errors. AssignCommand :char Example 1: :int ***TYPE ERROR (incompatible types in assigncommand) Example 2: foo Ident SimpleV foo not found ***SCOPE ERROR: undeclared variable foo

62. 62 3) Code Generation Assumes that program has been thoroughly checked and is well formed (scope & type rules) Takes into account semantics of the source language as well as the target language. Transforms source program into target code. Code Generation Decorated Abstract Syntax Tree Object Code

63. 63 3) Code Generation let var n: integer; var c: char in begin c := ‘&’; n := n+1 end PUSH 2 LOADL 38 STORE 1[SB] LOAD 0 LOADL 1 CALL add STORE 0[SB] POP 2 HALT n Ident SimpleT VarDecl Integer address = 0[SB]

64. 64 Compiler Passes A pass is a complete traversal of the source program, or a complete traversal of some internal representation of the source program. A pass can correspond to a “phase” but it does not have to! Sometimes a single “pass” corresponds to several phases that are interleaved in time. What and how many passes a compiler does over the source program is an important design decision.

65. 65 Single Pass Compiler Compiler Driver Syntactic Analyzer calls Contextual AnalyzerCode Generator calls Dependency diagram of a typical Single Pass Compiler: A single pass compiler makes a single pass over the source text, parsing, analyzing and generating code all at once.

66. 66 Multi Pass Compiler Compiler Driver Syntactic Analyzer calls Contextual AnalyzerCode Generator calls Dependency diagram of a typical Multi Pass Compiler: A multi pass compiler makes several passes over the program. The output of a preceding phase is stored in a data structure and used by subsequent phases. input Source Text output AST input output Decorated AST input output Object Code

67. 67 The Mini Triangle Compiler Driver public class Compiler { public static void compileProgram(...) { Parser parser = new Parser(...); Checker checker = new Checker(...); Encoder generator = new Encoder(...); Program theAST = parser.parse(); checker.check(theAST); generator.encode(theAST); } public void main(String[] args) {... compileProgram(...)... } } public class Compiler { public static void compileProgram(...) { Parser parser = new Parser(...); Checker checker = new Checker(...); Encoder generator = new Encoder(...); Program theAST = parser.parse(); checker.check(theAST); generator.encode(theAST); } public void main(String[] args) {... compileProgram(...)... } }

68. 68 Compiler Design Issues Single PassMulti Pass Speed Memory Modularity Flexibility “Global” optimization Source Language betterworse better for large programs (potentially) better for small programs worsebetter worse impossiblepossible single pass compilers are not possible for many programming languages

69. 69 Language Issues Example Pascal: Pascal was explicitly designed to be easy to implement with a single pass compiler: –Every identifier must be declared before it is first used. var n:integer; procedure inc; begin n:=n+1 end Undeclared Variable! procedure inc; begin n:=n+1 end; var n:integer; ?

70. 70 Language Issues Example Pascal: –Every identifier must be declared before it is used. –How to handle mutual recursion then? procedure ping(x:integer) begin... pong(x-1);... end; procedure pong(x:integer) begin... ping(x);... end;

71. 71 Language Issues Example Pascal: –Every identifier must be declared before it is used. –How to handle mutual recursion then? forward procedure pong(x:integer) procedure ping(x:integer) begin... pong(x-1);... end; procedure pong(x:integer) begin... ping(x);... end; OK!

72. 72 Language Issues Example Java: –identifiers can be declared before they are used. –thus a Java compiler needs at least two passes Class Example { void inc() { n = n + 1; } int n; void use() { n = 0 ; inc(); } }

73. 73 Scope of Variable Range of program that can reference that variable (ie access the corresponding data object by the variable’s name) Variable is local to program or block if it is declared there Variable is non-local to program unit if it is visible there but not declared there

74. 74 Static vs. Dynamic Scope Under static, sometimes called lexical, scope, sub1 will always reference the x defined in big Under dynamic scope, the x it references depends on the dynamic state of execution procedure big; var x: integer; procedure sub1; begin {sub1}... x... end; {sub1} procedure sub2; var x: integer; begin {sub2}... sub1;... end; {sub2} begin {big}... sub1; sub2;... end; {big}

75. 75 Static Scoping Scope computed at compile time, based on program text To determine the name of a used variable we must find statement declaring variable Subprograms and blocks generate hierarchy of scopes –Subprogram or block that declares current subprogram or contains current block is its static parent General procedure to find declaration : –First see if variable is local; if yes, done –If non-local to current subprogram or block recursively search static parent until declaration is found –If no declaration is found this way, undeclared variable error detected

76. 76 Example program main; var x : integer; procedure sub1; var x : integer; begin { sub1 } … x … end; { sub1 } begin { main } … x … end; { main }

77. 77 Dynamic Scope Now generally thought to have been a mistake Main example of use: original versions of LISP –Scheme uses static scope –Perl allows variables to be declared to have dynamic scope Determined by the calling sequence of program units, not static layout Name bound to corresponding variable most recently declared among still active subprograms and blocks

78. 78 Example program main; var x : integer; procedure sub1; begin { sub1 } … x … end; { sub1 } procedure sub2; var x : integer; begin { sub2 } … call sub1 … end; { sub2 } … call sub2… end; { main }

79. 79 Binding Binding: an association between an attribute and its entity Binding Time: when does it happen? … and, when can it happen?

80. 80 Binding of Data Objects and Variables Attributes of data objects and variables have different binding times If a binding is made before run time and remains fixed through execution, it is called static If the binding first occurs or can change during execution, it is called dynamic

81. 81 Binding Time Static Language definition time Language implementation time Program writing time Compile time Link time Load time Dynamic Run time –At the start of execution (program) –On entry to a subprogram or block –When the expression is evaluated –When the data is accessed

82. 82 X = X + 10 Set of types for variable X Type of variable X Set of possible values for variable X Value of variable X Scope of X –lexical or dynamic scope Representation of constant 10 –Value (10) –Value representation (1010 2 ) big-endian vs. little-endian –Type (int) –Storage (4 bytes) stack or global allocation Properties of the operator + –Overloaded or not

83. 83 Little- vs. Big-Endians Big-endian –A computer architecture in which, within a given multi-byte numeric representation, the most significant byte has the lowest address (the word is stored `big-end-first'). –Motorola and Sun processors Little-endian –a computer architecture in which, within a given 16- or 32-bit word, bytes at lower addresses have lower significance (the word is stored `little-end-first'). –Intel processors from The Jargon Dictionary - http://info.astrian.net/jargon

84. 84 Binding Times summary Language definition time: –language syntax and semantics, scope discipline Language implementation time: –interpreter versus compiler, –aspects left flexible in definition, –set of available libraries Compile time: –some initial data layout, internal data structures Link time (load time): –binding of values to identifiers across program modules Run time (execution time): –actual values assigned to non-constant identifiers The Programming language designer and compiler implementer have to make decisions about binding times

85. 85 Summary of today’s lecture Three topics –Treating Compilers and Interpreters as black-boxes Tombstone- or T- diagrams –A first look inside the black-box Your guided tour –Some Language Design Issues