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CS 331, Principles of Programming Languages. Introduction. Objectives. To introduce several different paradigms of programming But isn’t one language pretty much like another? No! To gain experience with these paradigms by using example programming languages

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objectives
Objectives
  • To introduce several different paradigms of programming
    • But isn’t one language pretty much like another? No!
  • To gain experience with these paradigms by using example programming languages
  • To understand concepts of syntax, translation, abstraction, and implementation
paradigms of programming
Paradigms of Programming?
  • There are several ways to think about computation:
    • a set of instructions to be executed
    • a set of expressions to be evaluated
    • a set of rules to be applied
    • a set of objects to be arranged
    • a set of messages to be sent and received
some programming paradigms
Some Programming Paradigms
  • Procedural
    • examples: C, Pascal, Basic, Fortran
  • Functional
    • examples: Lisp, ML
  • Object-oriented
    • examples: C++, Java, Smalltalk
  • Rule-based (or Logic)
    • example: Prolog
why so many
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 translators
models of computation
Models of Computation
  • RAM machine
    • procedural
  • directed acyclic graphs
    • Smalltalk model of O-O
  • partial recursive functions
    • Lisp and ML
  • Markov algorithms
    • Prolog is loosely based on these
lots of languages
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. bash, MATLAB
    • markup languages, e.g. HTML and XML
    • specification languages, e.g. UML
issues for all languages
Issues for all Languages
  • Can it be understood by people and processed by machines?
    • although translation may be required
  • Sufficient expressive power?
    • can we say what needs to be said, at an appropriate level of abstraction?
translation
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
trade offs
Trade-offs
  • Compilation
    • lower level machine may be faster, so programs run faster
    • compilation can be expensive
    • examples: C (and Java?)
  • Interpretation
    • more ability to perform diagnostics (or changes) at run-time
    • examples: Basic, UNIX shells, Lisp