CSE 428: Introduction and Overview
Introduction
The aim of the course is to offer a comparative overview
of the main programming paradigms:
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Functional
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Logical
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Imperative / Object-Oriented
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Concurrent / Distributed (time permitting)
For each paradigm, we will examine:
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Main characteristics
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Syntax
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Semantics
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Formal methods
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Implementation aspects
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Typical applications
For each paradigm we will consider one or two real programming language
for exercises and practice. We will not study any particular programming
language in detail: The purpose of the course is
not to learn the skills of programming in a particular language, but rather
to understand the general principles of programming languages. This
course should provide the ability to:
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learn new programming languages / new features
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choose the most appropriate language for a given
problem/resources
Overview of programming paradigms
The languages in blue
indicate the languages which we will probably choose for exercises and
practice during the course
Functional Programming
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Close to mathematical specification
Declarative: Program = specification of
the problem
(as opposed to the imperative style where
Program = specification of the sequence of
steps which the machine should perform in order to solve the problem)
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A program is a function/set of functions, usually
defined recursively
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Computation is the evaluation (simplification)
of expressions to values
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Languages: Lisp, Scheme, FP, Standard ML,
Askell,...
Logic Programming and Constraint Logic Programming
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Declarative. Even more declarative than functional
programming thanks to the following additional features:
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automatic backtracking
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unification / constraint solving
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A program is a logical theory
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Computation is proof search
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Languages: Prolog,
Lambda Prolog, CLP(X)...
Imperative Programming
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State and sharing.
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Efficient implementations (space, time).
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A program is a sequence of commands (operations which
modify the state)
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Computation is state transformation
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Languages:
Ada,
Fortran, Basic, Algol,
Pascal,
Cobol, Modula,
C,
...
Object-Oriented Programming
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Like imperative programming, has notions of state
and command.
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Efficient implementations.
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A program is the specification of a set of objects:
their attributes, and the way they interact with each other
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Computation is transformation of the state of objects
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Languages: Small Talk, C++,
Java, ...
Concurrent and Distributed Programming
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Several approaches, both from the declarative and
the imperative traditions
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A program is the specification of a set of processes
and the way they communicate / interact with each other. Processes are
autonomous activities, in principle executed in parallel by different
processors
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Languages: Most commercial languages have concurrent
extensions (Parallel Pascal, ADA, Java, Concurrent ML,...) but they offer
only a very limited view of the aspects of Concurrent Programming. For
practice, we will consider some experimental language like PICT.
Levels of programming Languages
We can trace a brief history of programming languages according to their
generations.
First Generation: Machine Languages.
- The native language of machines.
- Binary representation.
- Machine dependent
Second Generation: Assembly Languages.
- Uses Mnemonics to abstract from binary representation
- Uses symbolic addresses to abstract from absolute adressing
Third Generation: High-level Languages.
- Uses Data and Control structures as high-level abstractions of
programming concepts coded directly in assembly languages
- Machine independence
- Examples: FORTRAN, Algol60, Algol68, Pascal, C, Ada, ...
Fourth Generation: Declarative Languages.
- Departs from traditional approach to programming languages by
using declarative notions from mathematics to provide the notion
of computation.
- Not an abstraction of a previous generation.
- Much harder to produce efficient implementations.
- Examples: Standard ML, Lisp, Haskel, Prolog, lambdaProlog
Fifth Generation Languages.
- Term coined by the Japanese in the early 1980's ("Fifth Generation
Project) during their attempt to develop of new style of programming
languages and new hardware on which to implement these languages.
- Examples: Constraint Logic Programming (CLP)?