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Programming paradigms презентация
Содержание
- 1. Programming paradigms
- 2. Specifying the WHAT Describe the Inputs Specific
- 3. Specifying the HOW Describe the Inputs Specific
- 4. Procedural programming Describes the details of
- 5. Procedural Programming: State Program State Collection of
- 6. C, C++, C#, Java Abstractions of typical
- 7. Illustrative Example Expression (to be computed) :
- 8. Declarative Programming Specifies WHAT is to be
- 9. Imperative vs Non-Imperative Functional/Logic style clearly separates
- 10. Procedural vs Functional Program: a sequence
- 11. Functional Style : Illustration Definition: Equations
- 12. Paradigm vs Language Imperative Style tsum :=
- 13. Bridging the Gap Imperative is not always
- 14. Analogy: Styles vs Formalisms Iteration
- 15. Logic Programming Paradigm edge(a,b). edge(a,c). edge(c,a). path(X,X). path(X,Y) :- edge(X,Y). path(X,Y) :- edge(X,Z), path(Z,Y).
- 16. Logic Programming A logic program defines
- 17. Append in Prolog append([], L, L).
- 18. Different Kinds of Queries Verification append:
- 19. More Queries Constraint solving append: list x
- 20. Object-Oriented Style Programming with Abstract Data Types
- 21. Procedural vs Object-Oriented Emphasis on procedural abstraction.
- 22. Integrating Heterogeneous Data In C, Pascal, etc.,
- 23. Comparison : Figures example Data Square side
- 24. Adding a new operation Data
- 25. Adding a new data representation Data
- 26. Procedural vs Object-Oriented New operations cause additive
- 27. Object-Oriented Concepts Data Abstraction (specifies behavior)
- 28. Example : Role of interface in decoupling
- 29. Client in Scheme (define (size C)
- 30. Suppliers and Client in Java Interface Collection
Specifying the WHAT Describe the Inputs Specific values Properties Describe the Outputs (as above) Describe the Relationships Between I x O As a possibly infinite table Equations and other predicates between
Слайд 2Specifying the WHAT
Describe the Inputs
Specific values
Properties
Describe the Outputs (as above)
Describe the
Relationships Between I x O
As a possibly infinite table
Equations and other predicates between input and output expressions
For a given input, output may not be unique
As a possibly infinite table
Equations and other predicates between input and output expressions
For a given input, output may not be unique
Слайд 3Specifying the HOW
Describe the Inputs
Specific values
Properties
Describe HOW the Outputs are produced
Models
of existing computers
Program State
Control Flow
A Few Abstractions
Block Structure
Recursion via a Stack
Program State
Control Flow
A Few Abstractions
Block Structure
Recursion via a Stack
Слайд 4Procedural programming
Describes the details of HOW the results are to
be obtained, in terms of the underlying machine model.
Describes computation in terms of
Statements that change a program state
Explicit control flow
Synonyms
Imperative programming
Operational
Fortran, C, …
Abstractions of typical machines
Control Flow Encapsulation
Control Structures
Procedures
No return values
Functions
Return one or more values
Recursion via stack
Describes computation in terms of
Statements that change a program state
Explicit control flow
Synonyms
Imperative programming
Operational
Fortran, C, …
Abstractions of typical machines
Control Flow Encapsulation
Control Structures
Procedures
No return values
Functions
Return one or more values
Recursion via stack
Слайд 5Procedural Programming: State
Program State
Collection of Variables and their values
Contents of variables
change
Expressions
Not expected to change Program State
Assignment Statements
Other Statements
Side Effects
Expressions
Not expected to change Program State
Assignment Statements
Other Statements
Side Effects
Слайд 6C, C++, C#, Java
Abstractions of typical machines
Control Flow Encapsulation
Control Structures
Procedures
No return
values
Functions
Return one or more values
Recursion via stack
Better Data Type support
Functions
Return one or more values
Recursion via stack
Better Data Type support
Слайд 7Illustrative Example
Expression (to be computed) : a + b + c
Recipe
for Computation
Account for machine limitations
Intermediate Location
T := a + b; T := T + c;
Accumulator Machine
Load a; Add b; Add c
Stack Machine
Push a; Push b; Add; Push c; Add
Account for machine limitations
Intermediate Location
T := a + b; T := T + c;
Accumulator Machine
Load a; Add b; Add c
Stack Machine
Push a; Push b; Add; Push c; Add
Слайд 8Declarative Programming
Specifies WHAT is to be computed abstractly
Expresses the logic of
a computation without describing its control flow
Declarative languages include
logic programming, and
functional programming.
often defined as any style of programming that is not imperative.
Declarative languages include
logic programming, and
functional programming.
often defined as any style of programming that is not imperative.
Слайд 9Imperative vs Non-Imperative
Functional/Logic style clearly separates WHAT aspects of a program
(programmers’ responsibility) from the HOW aspects (implementation decisions).
An Imperative program contains both the specification and the implementation details, inseparably inter-twined.
An Imperative program contains both the specification and the implementation details, inseparably inter-twined.
Слайд 10Procedural vs Functional
Program: a sequence of instructions for a von
Neumann m/c.
Computation by instruction execution.
Iteration.
Modifiable or updatable variables..
Computation by instruction execution.
Iteration.
Modifiable or updatable variables..
Program: a collection of function definitions (m/c independent).
Computation by term rewriting.
Recursion.
Assign-only-once variables.
Слайд 11Functional Style : Illustration
Definition: Equations
sumto(0) = 0
sumto(n) = n +
sumto(n-1)
Computation: Substitution and Replacement
sumto(2) = 2 + sumto (2-1) = 2 + sumto(1)
= 2 + 1 + sumto(1-1) = 2 + 1 + sumto(0)
= 2 + 1 + 0 = …
= 3
Computation: Substitution and Replacement
sumto(2) = 2 + sumto (2-1) = 2 + sumto(1)
= 2 + 1 + sumto(1-1) = 2 + 1 + sumto(0)
= 2 + 1 + 0 = …
= 3
Слайд 12Paradigm vs Language
Imperative Style
tsum := 0;
i := 0;
while (i < n)
do
i := i + 1;
tsum := tsum + I
od
Storage efficient
i := i + 1;
tsum := tsum + I
od
Storage efficient
Functional Style
func sumto(n: int): int;
if n = 0
then 0
else n + sumto(n-1)
fi
endfunc;
No Side-effect
Слайд 13Bridging the Gap
Imperative is not always faster, or more memory efficient
than functional.
E.g., tail recursive programs can be automatically translated into equivalent while-loops.
func xyz(n : int, r : int) : int;
if n = 0
then r
else xyz(n-1, n+r)
fi
endfunc
E.g., tail recursive programs can be automatically translated into equivalent while-loops.
func xyz(n : int, r : int) : int;
if n = 0
then r
else xyz(n-1, n+r)
fi
endfunc
Слайд 14Analogy: Styles vs Formalisms
Iteration
Tail-Recursion
General Recursion
Regular Expression
Regular Grammar
Context-free Grammar
Слайд 15Logic Programming Paradigm
edge(a,b).
edge(a,c).
edge(c,a).
path(X,X).
path(X,Y) :- edge(X,Y).
path(X,Y) :- edge(X,Z), path(Z,Y).
Слайд 16Logic Programming
A logic program defines a set of relations.
This “knowledge”
can be used in various ways by the interpreter to solve different “queries”.
In contrast, the programs in other languages
Make explicit HOW the “declarative knowledge” is used to solve the query.
In contrast, the programs in other languages
Make explicit HOW the “declarative knowledge” is used to solve the query.
Слайд 17 Append in Prolog
append([], L, L).
append([ H | T ], X,
[ H | Y ]) :-
append(T, X, Y).
True statements about append relation.
Uses pattern matching.
“[]” and “|” stand for empty list and cons operation.
append(T, X, Y).
True statements about append relation.
Uses pattern matching.
“[]” and “|” stand for empty list and cons operation.
Слайд 18Different Kinds of Queries
Verification
append: list x list x list
append([1],
[2,3], [1,2,3]).
Concatenation
append: list x list -> list
append([1], [2,3], R).
Concatenation
append: list x list -> list
append([1], [2,3], R).
Слайд 19More Queries
Constraint solving
append: list x list -> list
append( R,
[2,3], [1,2,3]).
append: list -> list x list
append(A, B, [1,2,3]).
Generation
append: -> list x list x list
append(X, Y, Z).
append: list -> list x list
append(A, B, [1,2,3]).
Generation
append: -> list x list x list
append(X, Y, Z).
Слайд 20Object-Oriented Style
Programming with Abstract Data Types
ADTs specify/describe behaviors.
Basic Program Unit:
Class
Implementation of an ADT.
Abstraction enforced by encapsulation..
Basic Run-time Unit: Object
Instance of a class.
Has an associated state.
Implementation of an ADT.
Abstraction enforced by encapsulation..
Basic Run-time Unit: Object
Instance of a class.
Has an associated state.
Слайд 21Procedural vs Object-Oriented
Emphasis on procedural abstraction.
Top-down design; Step-wise refinement.
Suited for programming
in the small.
Emphasis on data abstraction.
Bottom-up design; Reusable libraries.
Suited for programming in the large.
Слайд 22Integrating Heterogeneous Data
In C, Pascal, etc., use
Union Type /
Switch Statement
Variant Record Type / Case Statement
In C++, Java, Eiffel, etc., use
Abstract Classes / Virtual Functions
Interfaces and Classes / Dynamic Binding
Variant Record Type / Case Statement
In C++, Java, Eiffel, etc., use
Abstract Classes / Virtual Functions
Interfaces and Classes / Dynamic Binding
Слайд 23Comparison : Figures example
Data
Square
side
Circle
radius
Operation (area)
Square
side * side
Circle
PI * radius *
radius
Classes
Square
side
area
(= side * side)
Circle
radius
area
(= PI*radius*radius)
Слайд 24Adding a new operation
Data
...
Operation (area)
Operation (perimeter)
Square
4 *
side
Circle
2 * PI * radius
Circle
2 * PI * radius
Classes
Square
...
perimeter
(= 4 * side)
Circle
...
perimeter
(= 2 * PI * radius)
Слайд 25Adding a new data representation
Data
...
rectangle
length
width
Operation (area)
...
rectangle
length * width
Classes
...
rectangle
length
width
area
(= length * width)
Слайд 26Procedural vs Object-Oriented
New operations cause additive changes in procedural style, but
require modifications to all existing “class modules” in object-oriented style.
New data representations cause additive changes in object-oriented style, but require modifications to all “procedure modules”.
New data representations cause additive changes in object-oriented style, but require modifications to all “procedure modules”.
Слайд 27Object-Oriented Concepts
Data Abstraction (specifies behavior)
Encapsulation (controls visibility of names)
Polymorphism (accommodates
various implementations)
Inheritance (facilitates code reuse)
Modularity (relates to unit of compilation)
Inheritance (facilitates code reuse)
Modularity (relates to unit of compilation)
Слайд 28Example : Role of interface in decoupling
Client
Determine the number of elements
in a collection.
Suppliers
Collections : Vector, String, List, Set, Array, etc
Procedural Style
A client is responsible for invoking appropriate supplier function for determining the size.
OOP Style
Suppliers are responsible for conforming to the standard interface required for exporting the size functionality to a client.
Suppliers
Collections : Vector, String, List, Set, Array, etc
Procedural Style
A client is responsible for invoking appropriate supplier function for determining the size.
OOP Style
Suppliers are responsible for conforming to the standard interface required for exporting the size functionality to a client.
Слайд 29Client in Scheme
(define (size C)
(cond
( (vector? C) (vector-length C)
)
( (pair? C) (length C) )
( (string? C) (string-length C) )
( else “size not supported”) )))
(size (vector 1 2 (+ 1 2)))
(size ‘(one “two” 3))
( (pair? C) (length C) )
( (string? C) (string-length C) )
( else “size not supported”) )))
(size (vector 1 2 (+ 1 2)))
(size ‘(one “two” 3))
Слайд 30Suppliers and Client in Java
Interface Collection {int size(); }
class myVector extends
Vector
implements Collection {
}
class myString extends String
implements Collection {
public int size() { return length();}
}
class myArray implements Collection {
int[] array;
public int size() {return array.length;}
}
Collection c = new myVector(); c.size();
implements Collection {
}
class myString extends String
implements Collection {
public int size() { return length();}
}
class myArray implements Collection {
int[] array;
public int size() {return array.length;}
}
Collection c = new myVector(); c.size();
