Chapter 1 Theory of Programming Languages

Programming Language Theory 2014, kkman@sangji.ac.kr 1
Chapter 1 ::
Introduction
Origin : Michael L. Scott
School of Computer & Information Engineering,
Sangji University
Kwangman Ko
(kkman@sangji.ac.kr)

Reading 1, P40.
Reading 2, P40

1. Introduction, P41
Why are there so many programming languages?
– evolution - we've learned better ways of doing things over time
– socio-economic factors: proprietary interests, commercial advantage
– orientation toward special purposes
– orientation toward special hardware
– diverse ideas about what is pleasant to use

Introduction
What makes a language successful? , PP42-43.
– easy to learn(BASIC, Pascal, LOGO, Scheme)
– easy to express things, easy use once fluent, "powerful”
• C, Common Lisp, APL, Algol-68, Perl, …
– easy to implement (BASIC, Forth)
– possible to compile to very good (fast/small) code (Fortran)
– backing of a powerful sponsor (COBOL, PL/1, Ada, Visual Basic)
– wide dissemination at minimal cost (Pascal, Turing, Java)

1.2 Program Language Spectrum, PP45-46.
Classified into families based on Model of Computation
– Declarative Programming Language
• focused on WHAT the computer is to do.
• More higher level, tune with the programmer’s point of view.
– Imperative Programming Language
• focused on HOW the computer should do it.
• dominate, mainly for performance reasons

Declarative programming language
– Functional
• Scheme, ML, pure Lisp, FP, …
– logic, constraint-based:
– Prolog, VisiCalc, RPG, …
Imperative programming language
– von Neumann:
• Fortran, Pascal, Basic, C, …
– object-oriented:
• Smalltalk, Eiffel, C++, …
– scripting languages:
• Perl, Python, JavaScript, PHP, …

1.3 Why study programming languages?, P47~
Help you choose a language.
– for systems programming
• C vs. Modula-3 vs. C++
– for numerical computations
• Fortran vs. APL vs. Ada
– for embedded systems
• Ada vs. Modula-2
– for symbolic data manipulation
• Common Lisp vs. Scheme vs. ML
– for networked PC programs
• Java vs. C/CORBA

Reading, P48.
– Understand OBSCURE features:
– Choose among alternative ways to express things
• understand implementation costs
– Make good use of debuggers, assemblers, linkers, and related tools
– Simulate useful features in languages that lack them

1.4 Compilation vs. Interpretation
Compilation vs. Interpretation
– not opposites
– not a clear-cut distinction
Source Program Compiler
Input Data
Outputs
Target Program
Source Program
Interpreter
Input Data
Outputs

Compilation vs. Interpretation
Pure Compilation
– translates the high-level source program into an equivalent target
program(typically in machine language).
원시
프로그램
목적
프로그램
Frontend
Backend
중간코드
COMPILER

Pure Interpretation
– stays around for the execution of the program
– the locus of control during execution
Reading, P51.
– Interpretation
• Greater flexibility
• Better diagnostics (error messages)
– Compilation
• Better performance

Most language implementations, ☞ P 51.
– a mixture of both compilation and interpretation
– compilation or simple pre-processing, followed by interpretation
source program
translator
intermediate program Virtual Machine
(interpreter)
Input Data
Output

source program
translator
intermediate program Virtual Machine
(interpreter)
Input Data
Output
Test.java
Java compiler
(javac Test.java )
Test.class Java interpreter
(java Test.class)

Preprocessor
– Removes comments and white space
– Groups characters into tokens (keywords, identifiers, numbers, symbols)
– Expands abbreviations in the style of a macro assembler
– Identifies higher-level syntactic structures (loops, subroutines)

Library of Routines and Linking
– Reading, P52.
– Compiler uses a linker program to merge the appropriate library of subroutines
(e.g., math functions such as sin, cos, log, etc.) into the final program:
source program
compiler
Incomplete
machine program
LINKER
Library Routines
machine program

Post-compilation Assembly
– Facilitates debugging (assembly language easier for people to read)
– Isolates the compiler from changes in the format of machine language files (only
assembler must be changed, is shared by many compilers)

The C Preprocessor (conditional compilation)
– Preprocessor deletes portions of code, which allows several versions of a program
to be built from the same source

Source-to-Source Translation (C++)
– C++ implementations based on the early AT&T compiler generated an
intermediate program in C, instead of an assembly language:

Bootstrapping

Dynamic and Just-in-Time(JIT) Compilation
– Reading, P56.
– In some cases a programming system may deliberately delay compilation until the
last possible moment.
– The Java language definition defines a machine-independent intermediate form
known as byte code. Byte code is the standard format for distribution of Java
programs.
– The main C# compiler produces .NET Common Intermediate Language (CIL),
which is then translated into machine code immediately prior to execution.

Compilation vs. Interpretation
Tools

1.5 Programming Environments

1.6 An Overview of Compilation, PP59-60.

Chapter 1 Theory of Programming Languages

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