Programming Languages

How I Started

Assembly

  • Represents low level processor operations directly
  • With minor syntactic sugar
  • Non-portable (must be heavily rewritten for every new system)
  • Hard to debug
  • Can produce very fast or very slow code depending on the expertise of the writer

Compiled

  • Code is turned into a binary executable
  • This binary is then run

Interpreted

  • Code is passed to an interpreter
  • The code is run inside the interpreter

Statically typed

  • The type of data that variables hold is static
  • i.e. it must not change for the life of the variable
  • most of the time it implies that the variable type must be explicitly provided

Dynamically typed

  • The type of variables could change at any moment
  • The type is checked whenever the variable is used
  • Flexible but slower (and
int a = 54;
float b = 12.3;
float c = a + b;

a = 54
b = 12.3
c = a + b

c = "Hello World"

d = c + a # Error !

C or C++

Python

Interpreted vs. compiled

  • Interpreted languages are often dynamically typed
  • Interpreted languages offer faster development as code can be executed and tested in a faster workflow
  • But interpreted languages offer this flexibility often at the cost of execution speed

Compiled

  • C
  • C++
  • Objective C
  • Java
  • SmallTalk
  • Processing
  • "Arduino"

Interpreted

  • Python
  • Lua
  • Lisp
  • Go
  • Javascript
  • Basic

General purpose

  • Provide general functionality for any purpose
  • Can often be extended to offer additional specific functionality

Domain specific

  • Language provides higher level abstractions for a specific domain
  • Domain specific operations become simpler
  • General purpose programming generally becomes harder

Domain specific languages

  • R, SSPS (Statistics and numerical computation)
  • Mathematica, Octave, MATLAB
  • Csound
  • Dot
  • Scratch
  • Pure Data/MAX etc.

Behind the scenes code generation

Extensions to general purpose languages

  • So many!!!
  • Numpy and Scipy for Python (numerical/scientific computation)
  • OpenGL libraries
  • Basically make code that is often reused, reusable.
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