🗊Презентация Principles of programming. Languages introduction. Objectives

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Слайд 1


CS 331, Principles of Programming Languages Introduction
Описание слайда:
CS 331, Principles of Programming Languages Introduction

Слайд 2


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
Описание слайда:
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

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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
Описание слайда:
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

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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
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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

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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
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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

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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
Описание слайда:
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

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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
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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

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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?
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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?

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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
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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

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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
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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

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