• History of, rationale for development and use of dynamic, interpreted (scripting) languages
• General characteristics of dynamic languages
• Advantages / disadvantages of dynamic languages
• Application of dynamic languages

• Some current open source languages and technologies
  • Perl
  • Python
  • PHP
  • Ruby
  • JavaScript
  • Lua

• Significant market demand for “Scripting” language skills

• Display terminals running interactive shells developed in the 1960-70s
  • Examples: IBM 2260, Hazeltine 2000, DEC VT52
  • Led to demand for scripts to relieve human operators of tedious, repetitive typing of commands
    • Led to shell scripting languages and DOS batch files
    • Eventually, general programming language features were added:
      • variables and structures (loops, conditionals)
    • The REXX scripting language started out as a scripting language on IBM mainframes.
      • Sample REXX code (written around 1995)

• Certain applications made scripting languages available to allow the creation of extensions and macros
  • emacs and its use of Lisp
  • Microsoft Office applications and their use of Visual Basic for Applications

• Processing text-based records one of the oldest uses of scripting languages
  • Led to development of several standard UNIX tools: awk, sed, grep
  • Perl was developed initially to address limitations in the standard text processing UNIX tools.
  • Regular expressions are an important part of the text processing tasks performed by scripting languages.

• The growth of the World Wide Web (server-side scripting)
  • Demand for dynamic (non-static) content
  • Led to the Common Gateway Interface (CGI) being provided by web servers, e.g. Apache
    • CGI programs required heavy text parsing, and dynamic languages like Perl were suited to that task
  • CGI had limitations (slow, needing to launch a new process for each Web request)
    • Led to different approaches to dynamic content delivery (Web scripting)
      • mod_perl, mod_python, ASP, PHP, JSP, Zope (Python), Ruby on Rails
  • Modern web browsers typically provide scripting languages to allow scripting of dynamic-type behaviors on web pages
    • ECMAScript (JavaScript), CSS and increasingly in HTML itself (HTML 5)
    • AJAX (use of JavaScript and XML to increase responsiveness of Web apps)

• Also called "dynamic programming languages"
• Languages that start as scripting languages can gain enough general programming features that they become suitable for general application development
  • Perl, Tcl, Lua
• Some are developed from scratch with general usage in mind.
  • Python, Ruby
• Still are often called “scripting languages”

(of dynamic programming languages, including “scripting” languages)

• Interpreted, rather than compiled
  • i.e., not directly executed but interpreted line-by-line by a language interpreter program which dynamically translates the instructions into machine-executable instructions “on the fly”
  • means that programs written in dynamic languages will execute much more slowly than compiled languages like C/C++ or more slowly than intermediate (byte-code compiled) languages like Java/C#
  • limits their use for very large applications
    • Though large applications are still written in dynamic languages, especially in Python
      • including media players, games, bittorrent clients
    • Components of or plug-ins to large applications are written in scripting languages.

• Dynamically or “weakly” typed
  • vs. statically or “strongly” typed (typical of compiled languages)
• Introduce variables or data structures as needed without the need to “declare” variables
• Variables start with generic type, often string
  • “Everything is a string.” applies to some scripting languages.
    • Shell scripting languages like bash, Tcl, Perl
  • “Everything is an object.” applies to other scripting languages.
    • Python, Ruby

(claimed)

• Allow accomplishing relatively simple tasks with a smaller amount of code
• Larger projects can be completed in a shorter amount of time
  • vs. compiled language
  • Assuming same programmer aptitude
  • Increased “programmer productivity”
  • Changes to code are quicker to test
  • Code is smaller, easier to understand

• Execution is slow, requires greater CPU/memory overhead
• Lack of strong typing can lead to unforeseen errors, errors which strong typing protects against