Outline. Compiler and Language Processing Tools. Language processing tools (2) Language processing tools. Language processing tools (3)

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Compiler and Language Processing Tools

Summer Term 2011

Introduction Prof. Dr. Arnd Poetzsch-Heffter

Software Technology Group TU Kaiserslautern

Prof. Dr. Arnd Poetzsch-Heffter Compilers 1

Introduction

Outline

1. Introduction

Language Processing Tools Application Domains

Tasks of Language-Processing Tools Examples

2. Language Processing

Terminology and Requirements Compiler Architecture 3. Compiler Construction

Prof. Dr. Arnd Poetzsch-Heffter Compilers 2

Introduction Language Processing Tools

Language processing tools

• Processing of source texts in (source) languages

• Analysis of (source) texts

• Translation to target languages

Prof. Dr. Arnd Poetzsch-Heffter Compilers 3

Introduction Language Processing Tools

Language processing tools (2)

Typical source languages

•Programming languages: C, C++, C#, Java, Scala, Haskell, ML, Smalltalk, Prolog

•Script languages: JavaScript, bash

•Languages for configuration management: make, ant

•Application and tool-specific languages: Excel, JFlex, CUPS •Specification languages: Z, CASL, Isabelle/HOL

•Formatting and data description languages: LaTeX, HTML, XML

•Design and architecture description languages: UML, SDL, VHDL, Verilog

Prof. Dr. Arnd Poetzsch-Heffter Compilers 4

Introduction Language Processing Tools

Language processing tools (3)

Typical target languages

• Assembly, machine, and bytecode languages

• Programming language

• Data and layout description languages • Languages for printer control

• ...

Prof. Dr. Arnd Poetzsch-Heffter Compilers 5

Introduction Language Processing Tools

Language processing tools (4)

Language implementation tasks

•Tool support for language processing

•Integration into existing systems

•Connection to other systems

Prof. Dr. Arnd Poetzsch-Heffter Compilers 6

Introduction Application Domains

Application domains

• Programming environments

I Context-sensitive editors, class browers I Graphical programming tools I Pre-processors

I Compilers

I Interpreters

I Debuggers

I Run-time environments (loading, linking, execution, memory management)

Prof. Dr. Arnd Poetzsch-Heffter Compilers 7

Introduction Application Domains

Application domains (2)

•Generation of programs from design documents (UML)

•Program comprehension, re-engineering

•Design and implementation of domain-specific languages

I Robot control

I Simulation tools

I Spread sheets, active documents

•Web technology

I Analysis of Web sites

I Active Web sites (with integrated functionality)

I Abstract platforms, e.g. JVM, .NET I Optimization of caching

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Introduction Application Domains

Related fields

• Formal languages, language specification and design

• Programming and specification languages

• Programming, software engineering, software generation, software architecture

• System software, computer architecture

Prof. Dr. Arnd Poetzsch-Heffter Compilers 9

Introduction Tasks of Language-Processing Tools

Tasks of Language-Processing Tools

Analyser Translation Interpreter

Source Code Source Code

Target Code Analysis

Results

Source Code Input Data

Output Data

Analysis, translation and interpretation are often combined.

Prof. Dr. Arnd Poetzsch-Heffter Compilers 10

Introduction Tasks of Language-Processing Tools

Tasks of Language-Processing Tools (2)

1. Translation

I Compiler implements analysis and translation

I OS and real machine implement interpretation Pros:

I Most efficient solution

I One interpreter for different programming languages

I Prerequisite for other solutions

Prof. Dr. Arnd Poetzsch-Heffter Compilers 11

Introduction Tasks of Language-Processing Tools

Tasks of Language-Processing Tools (3)

2. Direct interpretation

I Interpreter implements all tasks.

I Examples: JavaScript, command line languages (bash)

I Pros: No translation necessary (but analysis at run-time)

Prof. Dr. Arnd Poetzsch-Heffter Compilers 12

Introduction Tasks of Language-Processing Tools

Tasks of Language-Processing Tools (4)

3. Abstract and virtual machines

I Compiler implements analysis and translation to abstract machine

code

I Abstract machine works as interpreter I Examples: Java/JVM, C#, .NET I Pros:

•Platform independent (portability, mobile code)

•Self-modifing programs possible 4. Other combinations

Prof. Dr. Arnd Poetzsch-Heffter Compilers 13

Introduction Examples

Example: Analysis

17.04.2007 © A. Poetzsch-Heffter, TU Kaiserslautern 8 package b1_1 ; class Weltklasse extends Superklasse implement BesteBohnen {Qualifikation studieren ( Arbeit schweiss) { return new Qualifikation ();}} Beispiel: (Analyse) javac-Analysator S u p e rk la s s e .c la ss Q u a lif ik a tio n .c la ss A rb e it .c la s s B e s te B o h n e n .c la s s ... b1_1/Weltklasse.java:4: '{' expected. extends Superklasse ^ 1 error

Prof. Dr. Arnd Poetzsch-Heffter Compilers 14

Introduction Examples

Example: Translation

17.04.2007 © A. Poetzsch-Heffter, TU Kaiserslautern 9 package b1_1; class Weltklasse extends Superklasse implements BesteBohnen { Qualifikation studieren ( Arbeit schweiss ) { return new Qualifikation(); }} Beispiel 1: (Übersetzung) javac S u p e rk la s s e .c la ss Q u a lif ik a tio n .c la ss A rb e it .c la s s B e s te B o h n e n .c la s s ...

Compiled from Weltklasse.java class b1_1/Weltklasse extends ... implements ... { b1_1/Weltklasse(); b1_1.Qualifikation studieren(...); } Method b1_1/Weltklasse() ...

Method b1_1.Qualifikation studieren(...) ...

Prof. Dr. Arnd Poetzsch-Heffter Compilers 15

Introduction Examples

Example: Translation (2)

Result of translation17. 04. 2007 10 © A . P o e tz sch -H e ffte r, T U K a ise rsl a u te rn B e isp ie l 1 : (F o rts e tz u n g )

Compiled from Weltklasse.java class b1_1/Weltklasse extends b1_1.Superklasse implements b1_1.BesteBohnen { b1_1/Weltklasse(); b1_1.Qualifikation studieren(b1_1.Arbeit); } Method b1_1/Weltklasse() 0 aload_0

1 invokespecial #6 <Method b1_1.Superklasse()> 4 return

Method b1_1.Qualifikation studieren(b1_1.Arbeit) 0 new #2 <Class b1_1.Qualifikation>

3 dup

4 invokespecial #5 <Method b1_1.Qualifikation()> 7 areturn

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Introduction Examples

Example 2: Translation

17.04.2007 © A. Poetzsch-Heffter, TU Kaiserslautern 11 int main() {

printf("Willkommen zur Vorlesung!"); return 0; } Beispiel 2: (Übersetzung) gcc .file "hello_world.c" .version "01.01" gcc2_compiled.: .section .rodata .LC0:

.string "Willkommen zur Vorlesung!" .text .align 16 .globl main .type main,@function main: pushl %ebp movl %esp,%ebp subl $8,%esp ...

Prof. Dr. Arnd Poetzsch-Heffter Compilers 17

Introduction Examples

Example 2: Translation (2)

Result of translation 17.04.2007 © A. Poetzsch-Heffter, TU Kaiserslautern 12 Beispiel 2: (Fortsetzung) .file "hello_world.c" .version "01.01" gcc2_compiled.: .section .rodata .LC0:

.string "Willkommen zur Vorlesung!" .text .align 16 .globl main .type main,@function main: pushl %ebp movl %esp,%ebp subl $8,%esp addl $-12,%esp pushl $.LC0 call printf addl $16,%esp xorl %eax,%eax jmp .L2 .p2align 4,,7 .L2: movl %ebp,%esp popl %ebp ret .Lfe1: .size main,.Lfe1-main

.ident "GCC: (GNU) 2.95.2 19991024 (release)"

Prof. Dr. Arnd Poetzsch-Heffter Compilers 18

Introduction Examples

Example 3: Translation

17.04.2007 © A. Poetzsch-Heffter, TU Kaiserslautern 13 Beispiel 3: (Übersetzung) \documentclass{article} \begin{document} \vspace*{7cm}

\centerline{\Huge\bf It‘s groovy} \end{document}

groovy.tex (104 bytes)

...

groovy.dvi (207 bytes, binary)

%!PS-Adobe-2.0 %%Creator: dvips(k) 5.86 ... %%Title: groovy.dvi ... groovy.ps (7136 bytes) latex dvips

Prof. Dr. Arnd Poetzsch-Heffter Compilers 19

Introduction Examples

Example: Interpretation

17.04.2007 © A. Poetzsch-Heffter, TU Kaiserslautern 14 Beispiel: (Interpretation) ... 14 iload_1 15 iload_2 16 idiv 17 istore_3 ... .class-Datei Eingabedaten Ausgabedaten ... 14 iload_1 15 iload_2 16 idiv 17 istore_3 ...

Java Virtual Machine (JVM) Input Data

Output Data

.class File

Prof. Dr. Arnd Poetzsch-Heffter Compilers 20

Introduction Examples

Example: Combined technique

Java implementation with just-in-time (JIT) compiler

17.04.2007 © A. Poetzsch-Heffter, TU Kaiserslautern 15 Kombinierte Implementierungstechnik: Java-Implementierung mit JIT-Übersetzer

Java-Überset-zungseinheit javac Analysator Übersetzer Eingabedaten

Java Byte Code .class-Datei

Ausgabedaten JIT-Übersetzer

JVM

Maschinencode reale Maschine/Hardware (JIT=Just in time)

Beispiel: (Kombinierte Technik)

Java Source Code Unit Analyzer Translator Input Data Output Data .class file JIT Translator

Machine Code Real Machine / Hardware

Prof. Dr. Arnd Poetzsch-Heffter Compilers 21

Language Processing Terminology and Requirements

Language processing: The task of translation

Translator Source Code

Error Message or Target Code

Translator(in a broader sense): Analysis, optimization and translation

Source code:

Input (string) for translator in syntax of source language (SL)

Target Code:

Output (string) of translator in syntax of target language (TL)

Prof. Dr. Arnd Poetzsch-Heffter Compilers 22

Language Processing Terminology and Requirements

Phases of language processing

• Analysis of input:

I Program text

I Specification

I Diagrams

• Dependant on target of implementation

I Transformation (XSLT, refactoring)

I Pretty printing, formatting

I Semantic analysis (program comprehension)

I Optimization I (Actual) translation

Prof. Dr. Arnd Poetzsch-Heffter Compilers 23

Language Processing Terminology and Requirements

Compile time vs. run-time

Compile time: during run-time of compiler/translator

Static: All information/aspects known at compile time, e.g.:

I Type checks

I Evaluation of constant expressions I Relative addresses

Run-time: during run-time of compiled program

Dynamic: All information that are not statically known, e.g.:

I Allocation of dynamic arrays

I Bounds check of arrays

I Dynamic binding of methods

I Memory management of recursive procedures

Fordynamic aspectsthat cannot be handled atcompile time, the

compiler generates code that handles these aspects atrun-time.

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Language Processing Terminology and Requirements

What is a

good compiler

?

Prof. Dr. Arnd Poetzsch-Heffter Compilers 25

Language Processing Terminology and Requirements

Requirements for translators

•Error handling (static/dynamic)

•Efficient target code

•Choice: Fast translation with slow code vs. slow translation with fast code

•Semantically correct translation

Prof. Dr. Arnd Poetzsch-Heffter Compilers 26

Language Processing Terminology and Requirements

Semantically correct translation

Intuitive definition: Compiled program behaves according to language definition of source language.

Formal definition:

• semSL: SL_Program×SL_Data→SL_Data

• semTL: TL_Program×TL_Data→TL_Data

• compile: SL_Program→TL_Program

• code: SL_Data→TL_Data

• decode: TL_Data→SL_Data

Semantic correctness:

semSL(P,D) = decode(semTL(compile(P), code(D)))

Prof. Dr. Arnd Poetzsch-Heffter Compilers 27

Language Processing Compiler Architecture

Compiler Architecture

Scanner Source Code as String Token Stream Parser

Name and Type Analysis Translator Code Generator Syntax Tree Decorated Syntax Tree (Close to SL) Intermediate Language Target Code as String Attribution & Optimization Attribution & Optimization Peep Hole Optimization Analysis Synthesis

Prof. Dr. Arnd Poetzsch-Heffter Compilers 28

Language Processing Compiler Architecture

Properties of compiler architectures

• Phases are conceptual units of translation

• Phases can be interleaved

• Design of phases depends on source language, target language and design decisions

• Phase vs.pass(phase can comprise more than one pass.)

• Separate translation of pogram parts (Interface information must be accessible.)

• Combination with other architecture decisions:

Common intermediate language

Prof. Dr. Arnd Poetzsch-Heffter Compilers 29

Language Processing Compiler Architecture

Common intermediate language

Source

Language 1 Language 2Source Language nSource

Intermediate Language Target

Language 1 Language 2Target Language mTarget ...

...

Prof. Dr. Arnd Poetzsch-Heffter Compilers 30

Language Processing Compiler Architecture

Dimensions of compiler construction

• Programming languages

I Sequential procedural, imperative, OO-languages I Functional, logical languages

I Parallel languages/language constructs

• Target languages/machines I Code for abstract machines I Assembler

I Machine languages (CISC, RISC, ...)

I Multi-processor/multi-core architectures

I Memory hierarchy

• Translation tasks: analysis, optimization, synthesis

• Construction techniques and tools: bootstrapping, generators • Portability, specification, correctness

Prof. Dr. Arnd Poetzsch-Heffter Compilers 31

Compiler Construction

Compiler construction techniques

1. Stepwise construction

I Construction with compiler for different language I Construction with compiler for different machine

I Bootstrapping

2. Compiler-compiler: Tools for compiler generation

I Scanner generators (regular expressions)

I Parser generators (context-free grammars) I Attribute evaluation generators (attribute grammar)

I Code generator generators (machine specification)

I Interpreter generators (semantics of language)

I Other phase-specific tools

3. Special programming techniques

I General technique: syntax-driven

I Special technique: recursive descend

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Compiler Construction

Stepwise construction

Programming typically depends on an existing compiler for the implementation language. For compiler construction, this does not hold in general.

Source, target, and implementation languages of compilers can be denoted in T-diagrams.

CL

SL TL

T-diagram denotes compiler from source languageSLto target languageTL(SL→TLcompiler) written in languageCL.

Prof. Dr. Arnd Poetzsch-Heffter Compilers 33

Compiler Construction

Construction with compiler for different language

•Given:C→ML(machine language) compiler inML •Construct:SL→MLcompiler inML

•Solution: DevelopSL→MLcompiler inC, translate that compiler fromC→MLby using the existingC→MLcompiler

C SL ML ML C ML ML SL ML to be developed existing by translation

Prof. Dr. Arnd Poetzsch-Heffter Compilers 34

Compiler Construction

Construction with compiler for different machine

• Construct:C→ML1compiler inML1 • Given

1. C→ML1compiler inC 2. C→ML2compiler inML2 • Method: constructcross compiler

First step C C ML1 ML2 C ML2 ML2 C ML1 cross compiler given given

Prof. Dr. Arnd Poetzsch-Heffter Compilers 35

Compiler Construction

Construction with compiler for different machine (2)

Second step C C ML1 ML2 C ML1 ML1 C ML1 resulting compiler given cross compiler

Prof. Dr. Arnd Poetzsch-Heffter Compilers 36

Compiler Construction

Bootstrapping

• Construct:SL→MLcompiler inML • Suppose: yet no compiler exists

• Method:

1. Construct partial languageSLiofSLsuch that SL0⊂SL1⊂SL2⊂. . .⊂SL

2. ImplementSL0compiler forMLinML 3. ImplementSLi+1compiler forMLinSLi 4. CreateSLi+1compiler forMLinML

Prof. Dr. Arnd Poetzsch-Heffter Compilers 37

Compiler Construction

Bootstrapping (2)

SL0 SL1 ML ML SL0 ML ML SL1 ML SL1 SL2 ML SL2 SL ML ML SL2 ML ML SL ML manually by extension by translation

Prof. Dr. Arnd Poetzsch-Heffter Compilers 38

Compiler Construction

Recommended reading

Wilhelm, Maurer:

• Chap. 1, Introduction (pp. 1–5)

• Chap. 6, Structure of Compilers (pp. 225 – 238) Appel

• Chap. 1, Introduction (pp. 3 – 14)

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