1 Abstract Data Types (ADT) 4 Why use the objects? The need for - - PDF document

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Programming in the large - Lecture 3

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Programming in the large

Bertrand Meyer

Last update: 16 April 2004

Programming in the large - Lecture 3

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Reading assignment for next week

OOSC2: Chapter 3: Modularity Chapter 6: Abstract Data Types

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Lecture 3: Abstract Data Types

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Abstract Data Types (ADT)

Why use the objects? The need for data abstraction Moving away from the physical representation Abstract data type specifications Applications to software design

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The first step

A system performs certain actions on certain data. Basic duality: Functions [or: Operations, Actions] Objects [or: Data]

Action Object Processor

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Finding the structure

The structure of the system may be deduced from an analysis of the functions (1) or the objects (2). Resulting analysis and design method: Process-based decomposition: classical (routines) Object-oriented decomposition

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Arguments for using objects

Reusability: Need to reuse whole data structures, not just operations Extendibility, Continuity: Objects remain more stable over time.

Employee information Hours worked Produce Paychecks Paychecks

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Object technology: A first definition

Object-oriented software construction is the approach to system structuring that bases the architecture of software systems on the types of

• bjects they manipulate — not on “the” function

they achieve.

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The O-O designer’s motto

Ask NOT first WHAT the system does: Ask WHAT it does it TO!

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Issues of object-oriented design

How to find the object types. How to describe the object types. How to describe the relations and commonalities between object types. How to use object types to structure programs.

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Description of objects

Consider not a single object but a type of objects with similar properties. Define each type of objects not by the objects’ physical representation but by their behavior: the services (FEATURES) they offer to the rest of the world. External, not internal view: ABSTRACT DATA TYPES

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The theoretical basis

The main issue: How to describe program objects (data structures): Completely Unambiguously Without overspecifying?

(Remember information hiding)

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A stack, concrete object

count representation (array_up) capacity

representation [count] := x “Push” x on stack representation: count := count + 1

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x x

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A stack, concrete object

count representation (array_up) capacity

representation [count] := x

free (array_down) 1 representation

“Push” x on stack representation: count := count + 1 representation [free] := x “Push” x on stack representation: free := free - 1

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x x x

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A stack, concrete object

count representation (array_up) capacity

representation [count] := x

free (array_down) 1 representation

n new (linked) item item previous item previous previous

“Push” x on stack representation: count := count + 1 representation [free] := x “Push” x on stack representation: free := free - 1 “Push” operation: new (n) n.item := x n.previous := last head := n

1

x

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Stack: An Abstract Data Type (ADT)

Types: STACK [G]

• - G: Formal generic parameter

Functions (Operations): put: STACK [G] × G → STACK [G] remove: STACK [G] → STACK [G] item: STACK [G] → G empty: STACK [G] → BOOLEAN new: STACK [G]

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Using functions to model operations

put

,

=

( )

s x s’

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Reminder: Partial functions

A partial function, identified here by →, is a function that may not be defined for all possible arguments. Example from elementary mathematics: inverse: ℜ → ℜ, such that inverse (x) = 1 / x

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The STACK ADT (continued)

Preconditions: remove (s: STACK [G]) require not empty (s) item (s: STACK [G]) require not empty (s) Axioms: For all x: G, s: STACK [G] item (put (s, x)) = x remove (put (s, x)) = s empty (new)

(or: empty (new) = True)

not empty (put (s, x))

(or: empty (put (s, x)) = False)

put (

, ) =

s x s’

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Exercises

Adapt the preceding specification of stacks (LIFO, Last-In First-Out) to describe queues instead (FIFO). Adapt the preceding specification of stacks to account for bounded stacks, of maximum size capacity. Hint: put becomes a partial function.

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End of lecture 3