Introduction to Programming Language Concept

Programming Domains

•Scientific applications•Business applications•Artificial intelligence•Systems programming•Web Software

Language Evaluation Criteria

•Readability: the ease with which programs can be read and understood

•Writability: the ease with which a language can be used to create programs

•Reliability: conformance to specifications (i.e., performs to its specifications)

•Cost: the ultimate total cost

Influences on Language Design

•Computer Architecture

–Languages are developed around the prevalent computer architecture, known as the von Neumann architecture

•Program Design Methodologies

–New software development methodologies (e.g., object-oriented software development) led to new programming paradigms and by extension, new programming languages

Computer Architecture Influence

•Well-known computer architecture: Von Neumann

•Imperative languages, most dominant, because of von Neumann computers

–Data and programs stored in memory

–Memory is separate from CPU

–Instructions and data are piped from memory to CPU

–Basis for imperative languages

•Variables model memory cells

•Assignment statements model piping

•Iteration is efficient

The von Neumann Architecture

Programming Methodologies Influences

•1950's and early 1960's: Simple applications; worry about machine efficiency

•Late 1960's: People efficiency became important; readability, better control structures

–structured programming

–top-down design and step-wise refinement

•Late 1970's: Process-oriented to data-oriented

–data abstraction

•Middle 1980's: Object-oriented programming

–Data abstraction + inheritance + polymorph

Implementation Methods

•Compilation

–Programs are translated into machine language; includes JIT systems

–Use: Large commercial applications

•Pure Interpretation

–Programs are interpreted by another program known as an interpreter

–Use: Small programs or when efficiency is not an issue

•Hybrid Implementation Systems

–A compromise between compilers and pure interpreters

–Use: Small and medium systems when efficiency is not the first concern

Compilation

•Translate high-level program (source language) into machine code (machine language)

•Slow translation, fast execution

•Compilation process has several phases:

–lexical analysis: converts characters in the source program into lexical units

–syntax analysis: transforms lexical units into parse trees which represent the syntactic structure of program

–Semantics analysis: generate intermediate code

–code generation: machine code is generated

Pure Interpretation

•No translation

•Easier implementation of programs (run-time errors can easily and immediately be displayed)

•Slower execution (10 to 100 times slower than compiled programs)

•Often requires more space

•Now rare for traditional high-level languages

•Significant comeback with some Web scripting languages (e.g., JavaScript, PHP)

Hybrid Implementation Systems

•A compromise between compilers and pure interpreters

•A high-level language program is translated to an intermediate language that allows easy interpretation

•Faster than pure interpretation

•Examples

–Perl programs are partially compiled to detect errors before interpretation

–Initial implementations of Java were hybrid; the intermediate form, byte code, provides portability to any machine that has a byte code interpreter and a run-time system (together, these are called Java Virtual Machine)

Summary

•The study of programming languages is valuable for a number of reasons:

–Increase our capacity to use different constructs

–Enable us to choose languages more intelligently

–Makes learning new languages easier

•Most important criteria for evaluating programming languages include:

–Readability, writability, reliability, cost

•The major methods of implementing programming languages are: compilation, pure interpretation, and hybrid implementation

Reference

Robert W. Sebesta - Concept of Programming Languages (Tenth Edition), Chapter 1