Languages and Compilers (SProg og Overs

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Languages and Compilers (SProg og Overs

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Title: Languages and Compilers (SProg og Overs

1
Languages and Compilers(SProg og Oversættere)

Bent Thomsen
Department of Computer Science
Aalborg University

With acknowledgement to Norm Hutchinson whose
slides this lecture is based on.
2
Todays 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
Terminology
Q Which programming languages play a role in
this picture?
Translator
input
output
source program
object program
A All of them!
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)

5
Tombstone diagrams Combination rules
6
Compilation
Example Compilation of C programs on an x86
machine
x86
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
Cross compilation
Example A C cross compiler from x86 to PPC
A cross compiler is a compiler which runs on one
machine (the host machine) but emits code for
another machine (the target machine).
x86
Q Are cross compilers useful? Why would/could we
use them?
9
Two Stage Compilation
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
10
Compiling a Compiler
Observation A compiler is a program! Therefore
it can be provided as input to a language
processor.Example compiling a compiler.
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
x86
Q Why are abstract machines useful?
12
Interpreters
Q Why are abstract machines useful? 1) Abstract
machines provide better platform independence
JVM x86
JVM PPC
x86
PPC
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
x86
Functional equivalence
Note we dont have to implement Ultima emulator
in x86 we can use a high-level language and
compile it.
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
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 gt easier to
compile to
more low-level than source language gt easy to
implement as an interpreter
Example A Java Development Kit for machine M

Java-gtJVM
JVM M
M
16
Interpretive Compilers
Example Here is how we use our Java Development
Kit to run a Java program P
JVM M
M
M
17
Portable Compilers
Example Two different Java Development Kits
Kit 1
JVM M
Kit 2
JVM M
Q Which one is more portable?
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
dissimilar machine.
In practice 100 portability is as good as
impossible.

19
Example a portable compiler kit
Portable Compiler Kit
JVM Java
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)
20
Example a portable compiler kit
JVM Java
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 M
M
21
Example a portable compiler kit
This is what we have now
JVM Java
JVM M
Now, how do we run our Tetris program?
22
Bootstrapping
Remember our portable compiler kit
JVM Java
JVM M
23
Bootstrapping
Q What can we do with a compiler written in
itself? Is that useful at all?
Same language!

By implementing the compiler in (a subset of) its
own language, we become less dependent on the
target platform gt more portable implementation.
But chicken and egg problem? How do to get
around that?
gt 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
Bootstrapping an Interpretive Compiler to
Generate M code
Our portable compiler kit
JVM Java
JVM M
M
25
Bootstrapping an Interpretive Compiler to
Generate M code (first approach)
Step 1 implement
by rewriting
Step 2 compile it
JVM M
M
Step 3 Use this to compile again
26
Bootstrapping an Interpretive Compiler to
Generate M code (first approach)
Step 3 Self compile the Java (in Java) compiler
JVM M
M
27
Bootstrapping an Interpretive Compiler to
Generate M code (second approach)
Idea we will build a two-stage Java -gt M
compiler.
We will make this by compiling
To get this we implement
and compile it
28
Bootstrapping an Interpretive Compiler to
Generate M code (second approach)
Step 1 implement
Step 2 compile it
JVM M
M
Step 3 compile this
29
Bootstrapping an Interpretive Compiler to
Generate M code (second approach)
Step 3 Self compile the JVM (in JVM) compiler
JVM M
M
30
Bootstrapping an Interpretive Compiler to
Generate M code
Step 4 Compile the Java-gtJVM compiler into
machine code
M
We are DONE!
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 dont 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)
Step 1 build a compiler for Ada-S in another
language
32
Full Bootstrap
33
Full Bootstrap
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
Full Bootstrap
Step 3a Build a full Ada compiler in Ada-S
Step 3b Compile with v2 compiler
M
From this point on we can maintain the compiler
in Ada. Subsequent versions v4,v5,... of the
compiler in Ada and compile each with the the
previous version.
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 an
compiler for our language on a different machine
HM but want to develop one for TM ?
We have
We want
Idea We can use cross compilation from HM to TM
to bootstrap the TM compiler.
36
Half Bootstrap
Idea We can use cross compilation from HM to M
to bootstrap the M compiler.
Step 1 Implement Ada-gtTM compiler in Ada
Step 2 Compile on HM
Ada-gtTM
HM
HM
37
Half Bootstrap
Step 3 Cross compile our TM compiler.
Ada-gtTM
TM
HM
From now on we can develop subsequent versions of
the compiler completely on TM
38
Bootstrapping to Improve Efficiency
The efficiency of programs and compilers Efficien
cy 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
version of it. We can then use bootstrapping to
improve performance of the compiler.
39
Bootstrapping to Improve Efficiency
We have
We implement
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
Write it in machine code
Write it in a lower level language and compile it
using an existing compiler
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
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
The Phases of a Compiler
Source Program
Syntax Analysis
Error Reports
Abstract Syntax Tree
Contextual Analysis
Error Reports
Decorated Abstract Syntax Tree
Code Generation
Object Code
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 lt-gt Syntax
Contextual analysis lt-gt Contextual constraints
Code generation lt-gt Semantics

44
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 Triangle program
into TAM code.

! This program is useless except for!
illustrationlet var n integer var c
charin begin c n n1end
45
1) Syntax Analysis
Source Program
Syntax Analysis
Error Reports
Abstract Syntax Tree
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)
46
1) Syntax Analysis -gt AST
Program
LetCommand
SequentialCommand
SequentialDeclaration
AssignCommand
AssignCommand
BinaryExpr
VarDecl
Char.Expr
VNameExp
Int.Expr
SimpleT
SimpleV
SimpleV
Ident
Ident
Ident
Ident
Ident
Ident
Ident
Op
Char.Lit
Int.Lit
n Integer c Char c n n 1
47
2) Contextual Analysis -gt Decorated AST
Abstract Syntax Tree
Contextual Analysis
Error Reports
Decorated 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 gt declaration
Expressions gt Type

48
2) Contextual Analysis -gt Decorated AST
Program
LetCommand
SequentialCommand
SequentialDeclaration
AssignCommand
int
AssignCommand
BinaryExpr
VarDecl
Char.Expr
VNameExp
Int.Expr
char
int
int
SimpleT
SimpleV
SimpleV
char
int
Ident
Ident
Ident
Ident
Ident
Ident
Ident
Op
Char.Lit
Int.Lit
n
c
n
n
Integer
Char
c

1
49
Contextual Analysis

Finds scope and type errors.

Example 1
AssignCommand
TYPE ERROR (incompatible types in
assigncommand)
char
int
Example 2
foo not found
SimpleV
SCOPE ERROR undeclared variable foo
Ident
foo
50
3) Code Generation
Decorated Abstract Syntax Tree
Code Generation
Object Code

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.

51
3) Code Generation
let var n integer var c charin begin c
n n1end
PUSH 2LOADL 38STORE 1SBLOAD 0LOADL 1CALL
addSTORE 0SBPOP 2HALT
address 0SB
Ident
Ident
n
Integer
52
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.

53
Single Pass Compiler
A single pass compiler makes a single pass over
the source text, parsing, analyzing and
generating code all at once.
Dependency diagram of a typical Single Pass
Compiler
Compiler Driver
calls
Syntactic Analyzer
calls
calls
Contextual Analyzer
Code Generator
54
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.
Dependency diagram of a typical Multi Pass
Compiler
Compiler Driver
calls
calls
calls
Syntactic Analyzer
Contextual Analyzer
Code Generator
55
Example The 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(...)
...
56
Compiler Design Issues
Single Pass
Multi Pass
Speed Memory Modularity Flexibility Global
optimization Source Language
better
worse
better for large programs
(potentially) better for small programs
worse
better
better
worse
impossible
possible
single pass compilers are not possible for many
programming languages
57
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 use.

?
procedure incbegin nn1end var ninteger
var ninteger procedure incbegin nn1end
Undeclared Variable!
58
Language Issues

Example Pascal
Every identifier must be declared before it is
used.
How to handle mutual recursion then?

procedure ping(xinteger)begin ... pong(x-1)
...end procedure pong(xinteger)begin ...
ping(x) ...end
59
Language Issues

Example Pascal
Every identifier must be declared before it is
used.
How to handle mutual recursion then?

forward procedure pong(xinteger) procedure
ping(xinteger)begin ... pong(x-1)
...end procedure pong(xinteger)begin ...
ping(x) ...end
OK!
60
Language Issues

Example Java
identifiers can be declared before they are used.
thus a Java compiler need at least two passes

Class Example void inc() n n 1 int
n void use() n 0 inc()
61
Scope of Variable

Range of program that can reference that variable
(ie access the corresponding data object by the
variables name)
Variable is local to program or block if it is
declared there
Variable is nonlocal to program unit if it is
visible there but not declared there

62
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
63
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

64
Example

begin main
x
end main

program main
var x integer
procedure sub1
var x integer
begin sub1
x
end sub1

65
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

66
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

67
Binding

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

68
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

69
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

70
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 (10102)
big-endian vs. little-endian
Type (int)
Storage (4 bytes)
stack or global allocation
Properties of the operator
Overloaded or not

71
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.n
et/jargon
72
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
73
Syntax Design Criteria

Readability
syntactic differences reflect semantic
differences
verbose, redundant
Writeability
concise
Ease of verifiability
simple semantics

Ease of translation
simple language
simple semantics
Lack of ambiguity
dangling else
Fortrans A(I,J)

74
Lexical Elements

Character set
Identifiers
Operators
Keywords
Noise words
Elementary data
numbers
integers
floating point
strings
symbols
Delimiters

Comments
Blank space
Layout
Free- and fixed-field formats

75
Some nitty gritty decisions

Primitive data
Integers, floating points, bit strings
Machine dependent or independent (standards like
IEEE)
Boxed or unboxed
Character set
ASCII, EBCDIC, UNICODE
Identifiers
Length, special start symbol (,...), type
encode in start letter
Operator symbols
Infix, prefix, postfix, precedence
Comments
REM, / /, //, !,
Blanks
Delimiters and brackets
Reserved words or Keywords

76
Syntactic Elements

Definitions
Declarations
Expressions
Statements
Separate subprogram definitions (Module system)
Separate data definitions
Nested subprogram definitions
Separate interface definitions

77
Overall Program Structure

Subprograms
shallow definitions
C
nested definitions
Pascal
Data (OO)
shallow definitions
C, Java, Smalltalk

Separate Interface
C, Fortran
ML, Ada
Mixed data and programs
C
Basic
Others
Cobol
Data description separated from executable
statements
Data and procedure division

78
Some more Programming Language Design Issues

A Programming model (sometimes called the
computer) is defined by the language semantics
More about this in the semantics course
Programming model given by the underlying system
Hardware platform and operating system
The mapping between these two programming models
(or computers) that the language processing
system must define can be influenced in both
directions
E.g. low level features in high level languages
Pointers, arrays, for-loops
Hardware support for fast procedure calls

79
Programming Language Implementation

Develop layers of machines, each more primitive
than the previous
Translate between successive layers
End at basic layer
Ultimately hardware machine at bottom
To design programming languages and compilers, we
thus need to understand a bit about computers -)

80
Why So Many Computers?

It is economically feasible to produce in
hardware (or firmware) only relatively simple
computers
More complex or abstract computers are built in
software
There are exceptions
EDS machine to run prolog (or rather WAM)
Alice Machine to run Hope

81
Machines

Hardware computer built out of wires, gates,
circuit boards, etc.
An elaboration of the Von Neumann Machine
Software simulated computer that implemented in
software, which runs on top of another computer

Von Neumann Machine

Data
Primitive Operations
Sequence Control
Data Access
Storage Management
Operating Environment

82
Memory and data

Memory
Registers
PC, data or address
Main memory (fixed length words 32 or 64 bits)
Cache
External
Disc, CD-ROM, memory stick, tape drives
Order of magnitude in access speed
Nanoseconds vs. milliseconds
Built-in data types
integers, floating point, fixed length strings,
fixed length bit strings

83
Hardware computer

Operations
Arithmetic on primitive data
Tests (test for zero, positive or negative)
Primitive access and modification
Jumps (unconditional, conditional, return)
Sequence control
Next instruction in PC (location counter)
Some instructions modify PC
Data access
Reading and writing
Words from main memory, Blocks from external
storage
Storage management
Wait for data or multi-programming
Paging
Cache (32K usually gives 95 hit rate)

84
Virtual Computers

How can we execute programs written in the
high-level computer, given that all we have is
the low-level computer?
Compilation
Translate instructions to the high-level computer
to those of the low-level
Simulation (interpretation)
create a virtual machine
Sometimes the simulation is done by hardware
This is called firmware

85
Micro Program interpretation and execution
Fetch next instruction
Decode instruction Operation and operands
Fetch designated operands
Branch to designated operation
Execute Primitive Operation
Execute Primitive Operation
Execute Primitive Operation
Execute Primitive Operation
Execute halt
86
A Six-Level Computer
Applications
Level 5
Application Level
Compilers, Editors, Navigators
Software
Level 4
Assembly Language Level
Assembler, Linker, Loader
Level 3
Operating System Machine Level
Operating System
Level 2
Instruction Set Architecture Level
Hardware
Microprogram or hardware
Level 1
Microarchitecture Level
Hardware
Level 0
Digital Logic Level
from Andrew S. Tanenbaum, Structured Computer
Organization, 4th Edition, Prentice Hall, 1999.
87
Keep in mind