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Exploring Programming Paradigms & Languages: A Comprehensive Overview

This chapter introduces various programming paradigms, from procedural to object-oriented to rule-based, and explores how humans think about computational problems. It covers models of computation, translation methods, trade-offs between compilation and interpretation, and provides web resources for further study.

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Exploring Programming Paradigms & Languages: A Comprehensive Overview

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  1. CS 331, Principles of Programming Languages Chapter 1

  2. Objectives • To introduce several different paradigms of programming • To gain experience with these paradigms by using example programming languages • To understand concepts of syntax, translation, abstraction, and implementation

  3. Paradigms of Programming? • There are several ways to think about computation: • set of instructions to be followed • set of expressions to be evaluated • a set of rules to be applied • a set of objects to be rearranged • a set of messages to be sent and received

  4. Some Programming Paradigms • Procedural • examples: C, Pascal, Basic, Fortran • Functional • examples: Lisp, ML • Object-oriented • examples: Simula, C++, Java • Rule-based • example: Prolog

  5. Why so many? • Most important: the choice of paradigm (and therefore language) depends on how humans best think about the problem • Other considerations: • efficiency • compatibility with existing code • availability of translation

  6. Models of Computation • RAM machine • procedural • DAGs • Smalltalk model of O-O • partial recursive functions • Lisp • Markov algorithms • Prolog is loosely based on these

  7. Lots of Languages • There are many programming languages out there • Lots of other PL-like objects • document languages, e.g. LaTeX, Postscript • command languages, e.g. csh, MATLAB • specification languages, e.g. Z, UML

  8. Translation • Compilation • Translate into instructions suitable for some other (lower level) machine • During execution, that machine maintains program state information • Interpretation • May involve some translation • Interpreter maintains program state

  9. Trade-offs • Compilation • lower level machine may be faster, so programs run faster • compilation can be expensive • examples: C (and maybe Java?) • Interpretation • more ability to perform diagnostics (or changes) at run-time • examples: Basic, shells, Lisp

  10. Web resources • Programming language research • http://www.cs.cmu.edu/afs/cs.cmu.edu/user/mleone/web/language-research.html • Free compilers and interpreters • http://cuiwww.unige.ch/OSG/info/FreeComp/fc/categorie.html

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