The most effective weapon that computing scientists have in their fight against complexity is abstraction. What is abstraction?
Sometimes abstraction is described as "remembering the 'what' and ignoring the 'how'".
Large complex systems can only be made understandable by decomposing them into modules. When viewed from the outside, each module should be simple, with the complexity hidden inside. We strive for modules that have simple interfaces that can be used without knowing the implementations.
Two kinds of abstraction are of interest to computing scientists: procedural abstraction and data abstraction.
When we develop an algorithm following the top-down approach, we are practicing procedural abstraction. At a high level, we break the problem up into several tasks. We give each task a name and state its requirements, but we do not worry about how the task is to be accomplished until we expand it at a lower level of our design.
When we code a task in a programming language, we will typically make each task a procedure (or function). Any other program component that calls the procedure needs to know its interface (name, parameters, assumptions, etc.) but does not need to know the procedure's internal implementation details. The internal implementation can be changed without affecting the caller.
In data abstraction, the focus is on the problem's data rather than the tasks to be carried out. We examine the concepts of data abstraction in the sections that follow.
In a language like Pascal or C, all data structures are visible. A programmer can define custom data types, yet their structure and values are known to other parts of the program. These are concrete data structures.
As an example, consider a collection of records about the employees of a company. Suppose we store these records in a global Pascal or C array. The array and all its elements are visible to all parts of the program. Any statement in the program can directly access and modify the elements of the array.
An abstract data structure is a module consisting of data and operations. The data are hidden within the module and can only be accessed by means of the operations. The data structure is called abstract because its name and its interface are known, but not its implementation. The operations are explicitly given; the values are only defined implicitly by means of the operations.
Abstract data structures support information hiding. Their implementation is hidden behind an interface that remains unchanged, even if the implementation changes.
The concept of encapsulation is related to the concept of information hiding. The data and the operations that manipulate the data are all combined in one place. That is, they are encapsulated within a module.
An abstract data structure has a state that can be manipulated by the operations. The state is a value, or collection of information, held by the abstract data structure.
As an example, again consider the collection of records about the employees of a company. Suppose we impose a discipline on our Pascal or C program, only allowing the collection of records to be accessed through a small group of procedures. Inside this group of procedures, the array of records can be manipulated directly. However, all other parts of the program must use one of the procedures in the group to manipulate the records in the collection. The fact that the collection is implemented with an array is (according to the discipline we imposed) hidden behind the interface provided by the group of procedures.
Now suppose we wish to modify our program and change the implementation from an array to a linked list or maybe to move the collection to a disk file. By approaching the design of the collection as an abstract data structure, we have limited the parts of the program that must be changed to the small group of procedures that used the array directly; other parts of the program are not affected.
As another example of an abstract data structure, consider a stack.
We provide operations like push
, pop
, and
empty
to allow a user of the stack to access and
manipulate it. Except for the code implementing these operations, we
disallow direct access to the concrete data structure that implements
the stack. The implementation might use an array, a linked list, or
some other concrete data structure; the actual implementation is
"hidden" from the user of the stack.
There is only one instance of an abstract data structure. Often we need to create multiple instances of an abstract data structure. For example, we might need to have a collection of employee records for each different department within a large company.
We need to go a step beyond the abstract data structure and define an abstract data type (ADT).
What do we mean by type?
Consider the built-in type INTEGER
in Pascal (or
int
in C). By declaring a Pascal variable to be of type
INTEGER
, we are specifying that the variable has the
characteristics of that type:
INTEGER
, a subset of the
mathematical set of integers,
INTEGER
, addition, multiplication, comparison for
equality, etc.
Suppose we declare a Pascal variable to have type
INTEGER
. By that declaration, we are creating a
container in the program's memory that, at any point in time, holds a
single value drawn from the INTEGER
domain. The contents
of this container can be operated upon by the INTEGER
operations. In a program, we can declare several INTEGER
variables: each variable may have a different value, yet all of them
have the same set of operations.
In the definition of a concrete data type, the values are the most prominent features. The values and their representations are explicitly prescribed; the operations on the values are often left implicit.
The opposite is the case in the definition of an abstract data type. The operations are explicitly prescribed; the values are defined implicitly in terms of the operations. A number of representations of the values may be possible.
Conceptually, an abstract data type is a set of entities whose logical behavior is defined by a domain of values and a set of operations on that domain. In the terminology we used above, an ADT is set of abstract data structures all of whom have the same domain of possible states and have the same set of operations.
We will refer to a particular abstract data structure from an ADT as an instance of the ADT.
The implementation of an ADT in a language like Pascal or C is similar to that discussed above for abstract data structures. In addition to providing operations to access and manipulate the data, we need to provide operations to create and destroy instances of the ADT. All operations (except create) must have as a parameter an identifier (e.g., a pointer) for the particular instance to be operated upon.
While Pascal and C do not directly support ADTs, the
The behavior of an ADT is defined by a set of operations that can be
applied to an instance of the ADT.
Each operation of an ADT can have inputs (i.e., parameters) and
outputs (i.e., results). The collection of information about the
names of the operations and their inputs and outputs is the
interface of the ADT.
To specify an ADT, we need to give:
There are two primary approaches for specifying the semantics of the
operations:
In some ways, the axiomatic approach is the more elegant of the two
approaches. It is based in the well-established mathematical fields
of abstract algebra and category theory. Furthermore, it defines the
new ADT independently of other ADTs. To understand the definition of
the new ADT it is only necessary to understand its axioms, not the
semantics of a model.
However, in practice, the axiomatic approach to specification becomes
very difficult to apply in complex situations. The constructive
approach, which builds a new ADT from existing ADTs, is the more
useful methodology for most practical software development situations.
To illustrate both approaches, let us look at a well-known ADT that we
studied in the introductory data structures course, the stack.
In this section we give an axiomatic specification of an unbounded
stack ADT. By unbounded, we mean that there is no maximum capacity
for the number of items that can be pushed onto an instance of a
stack.
Remember that an ADT specification consists of the name, sets,
signatures, and semantics.
In this specification, we are defining an ADT named
The sets (domains) involved in the
To specify the signatures for the operations, we use the notation for
mathematical functions. By a tuple like
We categorize the operations into one of four groups depending upon
their functionality:
For now, we assume that a mutator returns a distinct new instance of
the ADT with a state that is a modified version of the original
instance's state. That is, we are taking an applicative (or
functional or referentially transparent) approach to ADT
specifications.
Technically speaking, a destructor is not an operation of the ADT. We
can represent the other types of operations as functions on the sets
in the specification. However, we cannot define a destructor in that
way. But destructors are of pragmatic importance in the
implementation of ADTs, particularly in languages that do not have
automatic storage reclamation (i.e., garbage collection).
The signatures of the
Constructors:
Mutators:
Accessors:
Destructors:
The operation
The separation of the traditional "pop" into two functions has two
advantages:
Also note that operation
We can specify the semantics of the
The axioms are logical assertions that must always be true. Thus we
can write Axioms 3 and 4 more simply as:
The first two axioms express the last-in-first-out (LIFO) property of
stacks. Axiom 1 tells us that the top element of the stack is the
last element pushed. Axiom 2 tells us that removal of the top element
returns the stack to the state it had before the last push.
Moreover, axioms 1 and 2 specify the LIFO property of stacks in purely
mathematical terms; there was no need to use the properties of any
representation or any time-based (i.e., imperative) reasoning.
The last two axioms define when a stack is empty and when it not.
Axiom 3 tells us that a newly created stack is empty. Axiom 4 tells
us that pushing an entity on a stack results in a nonempty stack.
But what about the sequences of operations
Clearly we do not want to allow either
Functions may be either total or partial.
For example, the multiplication operation on the set of real numbers
For example, the division operation on the set of real numbers
In software development (and, hence, in specification of ADTs),
partial functions are common. To avoid errors in execution of such
functions, we need to specify the actual domain of the partial
functions precisely.
In an axiomatic specification of an ADT, we restrict operations to
their domains by using preconditions. The precondition of an
operation is a logical assertion that specifies the assumptions about
and the restrictions upon the values of the arguments of the
operation.
If the precondition of an operation is false, then the operation
cannot be safely applied. If any operation is called with its
precondition false, then the program is incorrect.
In the axiomatic specification of the stack, we introduce two
preconditions as follows.
Note that we have not given the semantics of the destructor operation
Operation
Another simplification that we have made in this ADT specification is
that we did not impose a bound on the capacity of the stack instance.
We could specify this, but it would also complicate the axioms
the specification.
In this section, we give a constructive specification of a bounded
stack ADT. By bounded, we mean that there is a maximum capacity for
the number of items that can be pushed onto an instance of a stack.
In this specification of bounded stacks, we have one additional set
involved, the set of integers.
In this specification of unbounded stacks, we define the
Constructors:
Mutators:
In this specification, we add operation
Accessors:
Destructors:
In the constructive approach, we give the semantics of each operation
by associating both a precondition and a postcondition with the
operation.
As before, the precondition is a logical assertion that
specifies the required characteristics of the values of the arguments.
A postcondition is a logical assertion that specifies the
characteristics of the result computed by the operation with respect
to the values of the arguments.
In this specification, we are a bit informal about the nature of the
underlying model. Although the presentation here is informal, we try
to be precise in the statement of the pre- and postconditions.
Note that each operation except the constructor (
Also note that all of these
Suppose we implement the mutator operations as imperative commands
rather then applicative functions. That is, we implement mutators so
that they directly modify the state of an instance instead of
returning a modified copy. (
Then, in some sense, the above "validity" property is
invariant for an instance of the ADT; the constructor makes
the property true, all mutators and accessors preserve its truth, and
the destructor makes it false.
An invariant property must hold between operations on the instance; it
might not hold during the execution of an operation. (For this
discussion, we assume that only one thread has access to the ADT
implementation.)
Aside: An invariant on an ADT instance is similar in concept to an
invariant for a while-loop. A loop invariant holds before and after
each execution of the loop.
As a convenience in specification we will sometimes state the
invariants of the ADT separately from the pre- and postconditions of
the methods. We sometimes will divide the invariants into two groups.
The interface invariants are part of the public interface of the ADT.
The implementation invariants are part of the hidden state of an
instance; in some cases, they define the meaning of the abstract
properties stated in the interface invariants in terms of hidden
values in the implementation.
A Java
Like the Pascal record type, a Java class can consist of several
components. In Pascal, all the components are data fields. However,
in Java, functions and procedures may be included as components of a
class. These procedures and functions are called methodsclass
construct provides a direct way to define ADTs in languages like C++
and Java.
.
Defining ADTs
Axiomatic Specification of an Unbounded Stack ADT
Name
Stack
(of Item
)
Stack
. The parameter Item
represents the
arbitrary unspecified type for the entities stored in the stack.
Item
is a formal generic parameter of the ADT
specification. Stack
is itself a generic ADT; a
different ADT is specified for each possible generic argument
that can be substituted for Item
.
Sets
Stack
ADT are
the following:
Stack
:
Item
:
boolean
:
{ False, True }
Signatures
(Stack, Item)
,
we mean the Cartesian product of sets Stack
and
Item
, that is, the set of ordered pairs where the first
component is from Stack
and the second is from
Item
. The set to the right of the ->
is the return type of the function.
We will normally list the operations in that order.
Stack
ADT operations are as
follows.
create: -> Stack
push: (Stack, Item) -> Stack
pop: Stack -> Stack
top: Stack -> Item
empty: Stack -> boolean
destroy: Stack ->
pop
may not be the same as the "pop"
operation you learned in a data structures class. The traditional
"pop" both removes the top element from the stack and returns it. In
this ADT, we have separated out the "return top" functionality into
accessor operation top
and left operation
pop
as a pure mutator operation that returns the modified
stack.
destroy
does not return a value.
As we pointed out above, the destroy
operation is not
really a part of the formal ADT specification.
Semantics (Axiomatic Approach)
Stack
ADT with the
following axioms. Each axiom must hold for all instances
s
of type Stack
and all entities
x
of type Item
.
top(push(s,x)) = x
pop(push(s,x)) = s
empty(create()) = True
empty(push(s,x)) = False
empty(create())
not empty(push(s,x))
top(create())
and pop(create())
?
top
or
pop
to be applied to an empty stack. That is,
top
and pop
are undefined when their
arguments are empty stacks.
A -> B
is defined for all
elements of A
.
R
is a total function (R,R) -> R
.
A -> B
is undefined for
one or more elements of A
.
R
is a partial function because it is undefined when the
divisor is 0
.
pop(Stack S)
:
not empty(S)
top(Stack S)
not empty(S)
destroy
. This operation cannot be handled in the simple
framework we have established.
destroy
is really an operation on the
"environment" that contains the stack. By introducing, the
"environment" explicitly into our specification, we could specify its
behavior more precisely. Of course, the semantics of
create
would also need to be extended to modify the
environment and the other operations would likely require
preconditions to ensure that the stack has been created in the
environment.
Constructive Specification of a Bounded Stack ADT
Name
StackB
(of Item
)
Sets
StackB
:
Item
:
boolean
:
int
:
{ ..., -2, -1, 0, 1, 2, ... }
Signatures
create
operation to take the maximum capacity as its
parameter.
create: int -> StackB
push: (StackB, Item) -> StackB
pop: StackB -> StackB
full
to detect
whether or not the stack instance has reached its maximum capacity.
top: StackB -> Item
empty: StackB -> boolean
full: StackB -> boolean
destroy: StackB ->
Semantics (Constructive Approach)
create(int size) -> StackB S'
size >= 0
S'
is a valid new instance of
StackB
&&
S'
has the capacity to store size
items &&
empty(S')
push(StackB S, Item I) -> StackB S'
S
is a valid StackB
instance &&
not full(S)
S'
is a valid StackB
instance &&
S' = S
with I
added as the new top.
pop(StackB S) -> StackB S'
S
is a valid StackB
instance &&
not empty(S)
S'
is a valid StackB
instance &&
S' = S
with the top item deleted
top(StackB S) -> Item I
S
is a valid StackB
instance &&
not empty(S)
I =
the top item on S
S
is not modified by this operation.)
empty(StackB S) -> boolean e
S
is a valid StackB
instance
e
is true
if and only if S
contains no elements (i.e., is empty)
S
is not modified by this operation.)
full(StackB S) -> boolean f
S
is a valid StackB
instance
f
is true
if and only if S
contains no space for additional items (i.e., is full)
S
is not modified by this operation.)
destroy(StackB S) ->
S
is a valid StackB
instance
StackB S
no longer exists
create
)
has a StackB
instance as an input; the constructor and
each of the mutators also has a StackB
instance as an
output. This parameter identifies the particular instance that the
operation is manipulating.
StackB
instances are required
to be "valid" in all preconditions and postconditions, except the
precondition of the constructor and the postcondition of the
destructor. By valid we mean that the state of the instance is within
the acceptable domain of values; it has not become corrupted or
inconsistent. What is specifically mean by "valid" will differ from
one implementation of a stack to another.
S
and S'
are
implemented as different states of the same physical instance.)
Java Classes
class
is similar to a user-defined record
type in Pascal. A class
is a template for
constructing data items that have the same structure but differing
values (states). We say that an item constructed by a class is a
class instance (or, as we see later, an object).
A method declared in a class may be either a class method or instance method.
We declare a method as a class method by giving the keyword
static
in the header of its definition.
For example, a main
method of a program is a class method
of the class in which it is defined.
public static void main(String[] args) { // beginning code for the program }
If we do not include the keyword static
in the
header of a method definition, the method is an instance
method. For example, consider methods to implement the
push
and top
operations of a class that
implements a stack.
public void pop() { // code for pop operation } public Object top() { // code for top operation }
Note that pop()
is a procedure (i.e., it has
return type void
) method and top
is a
function method.
In a similar fashion, the variables (data fields) declared in a class may be either class variables or instance variables.
static
is used to declare a
class variable.
static
denotes an
instance variable.
An instance method has access to the instance variables of the class instance (object) to which it is applied. The instance's variables are implicit arguments of the method calls. The instance methods also have access to the class variables (if any).
Class methods only have access to the class variables. The methods do not have any implicit arguments. In fact, class methods can be called without any instances of the class being in existence.
The components of a class can be designated as public
or
private
.
public
components of the class are accessible
from anywhere in the program.
private
components are only accessible from
inside the class.
As a general rule, the data fields of a class should be private instance variables, meaning that they are associated with a specific instance and are only accessible by the instance methods. This hides, or encapsulates, the data fields within the class instance.
Note: Actually, the instance methods of a class can access the instance variables of any instance of that class, not just the current instance.
In general, avoid public instance variables. They break the principle of information hiding, leading to potential entanglements among modules.
A public method of a class is a service provided by that instance to other parts of a program. The private methods of a class can be used in implementing the public methods.
Class methods and variables should be used sparingly. These are more or less the types of subprograms and global variables found in languages like Pascal and C. Their excessive use can greatly reduce the potential benefits that can be realized from object-oriented techniques.
Note: There are two other types of accessability, "friendly" and
protected
, but public
and
private
are sufficient for our purposes in discussion of
ADT implementations.
A Java variable is a strongly typed "container" in memory that is declared to hold either:
int
), booleans (boolean
), and
single characters (char
).
The class instances themselves are stored in the dynamically managed heap memory area. Java allocates memory from the heap to hold newly constructed instances of a class. Java's garbage collector reclaims the memory for instances that are no longer needed by the program.
One way to implement an ADT in Java is to do the following:
class
construct to represent the entire
ADT. If we want to allow access to the class from anywhere in the
program, we will make the class public
.
For the StackB
ADT, we can use the following structure for
the class:
public class StackB { // implementation of instance methods and data here }
For example, to declare a variable that can hold a reference to a
StackB
instance, we can use the following declaration:
StackB stk;
A Java constructor is a method with the same name as the class. It does not have a return type specified. Upon creation of an instance of the class, the constructor initializes the instance's state.
A constructor is normally invoked by the Java operator
new
. The operator new
allocates memory on
the heap for the instance, calls the constructor to initialize the new
instance, and then returns a reference to the new instance.
For example, we can represent the ADT operation
create
by the constructor method StackB
.
public class StackB { public StackB(int size) { // initialization code } // rest of StackB methods and data ... }
A user of the StackB
class can then declare a variable
and initialize it to hold a reference to a new stack with a capacity
of 100 items as follows:
StackB stk = new StackB(100);
The expression new StackB(100)
allocates a
StackB
instance in the heap storage and calls the
constructor above to initialize the data fields encapsulated within
the instance.
We can apply a method to a class instance by using the selector (i.e.,
"dot") notation. This notation is similar to the notation for
accessing record
components in Pascal.
For example, in the case of the StackB
ADT we can
represent the operations as instance methods of class
StackB
. The explicit StackB
parameters and
return values of the operations thus become implicit.
Suppose we want to push an item x
onto the stk
created above. We can do that with the following code:
if (!stk.full()) stk.push(x);
We can then examine the top item and remove it:
if (!stk.empty()) { it = stk.top(); stk.pop(); }
public
methods of the class. That is, precede the
method's definition by the keyword public
.
void
) methods, except those mutator operations that
explicitly require new instances to be generated (e.g., a copy
operation). These methods modify the encapsulated state of the class
instance (which is the implicit argument of the methods).
public void pop() { // code to implement operation }Comment: Implementing mutator operations as procedure calls that modify the stored state is really an optimization. All mutators can be implemented in the applicative style, returning a modified copy of the instance. This implementation might, however, be quite inefficient in use of processor time and memory.
public boolean empty() { // code to implement operation }
public void destroy() { // code to free resources }
private
data fields of the Java class to
represent the encapsulated state of the instance needed for a
particular implementation. By making the data fields
private
they are still available to the instance's
methods, but are not visible outside the class.
public class StackB { // public operations of class instance // encapsulated data fields of class instance private int topItem; // Pointer to next index for insertion private int capacity; // Maximum number of items in stack private Object[] stk; // the stack }
public
data fields in the class. They
violate the principle of information hiding. Instead introduce
appropriate accessor and mutator methods to allow manipulation of the
hidden state.
private
methods to aid in
implementation. Functionality common to several methods can be placed
in separate functions and procedures as needed. However, since these
are private
, they can only be accessed from within the
class and thus can be changed without affecting the public interface
of the class.
toString()
method to convert an instance of the ADT's
class to an appropriately valued Java String
for
printing.
Java does not currently have a parameterized class facility (like the
C++ template
or Ada generic
mechanisms). We
must handle the type parameters of the ADT in other ways.
For example, in the next section we represent the set
Item
of the StackB
ADT by the class
Object
. As we will see when we discuss inheritance, the
Object
type will allow us to store an instance of any
class on the StackB
. With this definition, any data of a
reference type can appear in the stack, but values of the primitive
types cannot.
In this section, we give an implementation of the StackB
ADT that uses an array of objects and an integer "pointer" to
represent the stack.
This implementation is not robust; each operation assumes that its precondition holds. A more robust implementation might check whether the precondition holds and throw an exception if it does not.
Remember that the invariants are implicitly pre- and postconditions of all mutator and accessor methods, postconditions of the constructor, and preconditions of the destructor.
// A Bounded Stack ADT public class StackB { // Interface Invariant: Once created and until destroyed, this // stack instance has a valid and consistent internal state public StackB(int size) // Pre: size >= 0 // Post: initialized new instance with capacity size && empty() { stk = new Object[size]; capacity = size; topItem = 0; } Public void push(Object I) // Pre: not full() // Post: I added as the new top of this instance's stack { stk[topItem] = I; topItem++; } public void pop() // Pre: not empty() // Post: item at top of stack removed from this instance { topItem--; stk[topItem] = null; } public Object top() // Pre: not empty() // Post: return item at top of this instance's stack { return stk[topItem-1]; } public boolean empty() // Pre: true // Post: return true iff this instance's stack has no elements { return (topItem <= 0); } public boolean full() // Pre: true // Post: return true iff this instance's stack is at full capacity { return (topItem >= capacity); } public void destroy() // Pre: true // Post: internal resources released; stack effectively deleted { stk = null; capacity = 0; topItem = 0; } // Implementation Invariants: 0 <= topItem <= capacity // stack is in array section stk[0..topItem-1] // with the top at stk[topItem-1], etc. private int topItem; // Pointer to next index for insertion private int capacity; // Maximum number of items in stack private Object[] stk; // the stack }
Consider an ADT for storing and manipulating calendar dates. We will
call the ADT Day
to avoid confusion with the
Date
class in the Java API. This ADT is based on the
Day
class defined in Chapter 4 of the first edition of
the book Core Java.
Logically, a calendar date consists of three pieces of information: a
year designator, a month designator, and a
day of the month designator. A secondary piece of
information is the day of the week. In this ADT interface definition,
we use integers (i.e., Java int
) to designate these
pieces of information.
create(int y, int m, int d) -> Day D'
y != 0 && 1 <= m <= 12 && 1 <= d <= #days in month m
&&
(y,m,d)
does not fall in the gap formed by the
change to the modern (Gregorian) calendar
D'
is a valid new instance of
Day
with year y
, month m
, and
day d
setDay(Day D, int y, int m, int d) -> Day D'
D
is a valid instance of Day
&&
y != 0 && 1 <= m <= 12 && 1 <= d <= #days in month
&&
(y,m,d)
does not fall in the gap formed by the
change to the modern (Gregorian) calendar
D'
is a valid instance of Day
&&
D'= D
except with
year y
, month m
, and day d
Question: Should we include setDay
,
setMonth
, and setYear
operations?
What problems might arise?
advance(Day D, int n) -> Day D'
D
is a valid instance of Day
D'
is a valid instance of Day
&&
D' = D
with the date moved
n
days later (Negative n
moves to an
earlier date.)
getDay(Day D) -> int d
D
is a valid instance of Day
d
is day of the month from D
, where
1 <= d <= #days in month getMonth(D)
D
is unchanged.)
getMonth(Day D) -> int m
D
is a valid instance of Day
m
is the month from D
, where
1 <= m <= 12
D
is unchanged.)
getYear(Day D) -> int y
D
is a valid instance of Day
y
is the year from D
, where
y != 0
D
is unchanged.)
getWeekday(Day D) -> int wd
D
is a valid instance of Day
wd
is the day of the week upon which
D
falls: 0 = Sunday, 1 = Monday, ..., 6 = Saturday
D
is unchanged.)
equals(Day D, Day D1) -> boolean eq
D
and D'
are valid instances of
Day
eq
is true if and only if D
and
D'
denote the same calendar date
D
and D'
are unchanged.)
daysBetween(Day D, Day D1) -> int d
D
and D'
are valid instances of
Day
d
is the number of calendar days from
D1
to D
, i.e.,
equals(D,advance(D1,d))
would be true
D
is unchanged.)
toString(Day D) -> String s
D
is a valid instance of Day
s
is the date D
expressed in the format
"Day[getYear(D)
,getMonth(D)
,getDay(D)
]".
D
is unchanged.)
destroy(Day D) ->
D
is a valid instance of Day
D
no longer exists
// Parts of this come unmodified from _Core_Java_ (First Edition). // Not all the commenting has been made consistent. import java.util.*; public class Day { // Interface Invariant: Once created and until destroyed, this // instance contains a valid date. getYear() != 0 && // 1 <= getMonth() <= 12 && 1 <= getDay() <= #days in getMonth(). // Also calendar date getMonth()/getDay()/getYear() does not // fall in the gap formed by the change to the modern // (Gregorian) calendar. // Constructors public Day() // Pre: true // Post: the new instance's day, month, and year set to today's // date (i.e., the date of creation of the instance) { java.util.Date today = new java.util.Date(); year = today.getYear() + 1900; month = today.getMonth() + 1; day = today.getDay(); } public Day(int y, int m, int d) throws IllegalArgumentException // Pre: y != 0 && 1 <= m <= 12 && 1 <= d <= #days in month m // (y,m,d) does not fall in the gap formed by the change // to the modern (Gregorian) calendar. // Post: the new instance's day, month, and year set to y, m, // and d, respectively // Exception: IllegalArgumentException if y m d not a valid date { year = y; month = m; day = d; if (!isValid()) throw new IllegalArgumentException(); } // Mutators public void setDay(int y, int m, int d) throws IllegalArgumentException // Pre: y != 0 && 1 <= m <= 12 && 1 <= d <= #days in month m // (y,m,d) does not fall in the gap formed by the // change to the modern (Gregorian) calendar. // Post: this instance's day, month, and year set to year, month // and day set to y, m, and d, respectively // Exception: IllegalArgumentException if y m d not a valid date { year = y; month = m; day = d; if (!isValid()) throw new IllegalArgumentException(); } public void advance(int n) // Pre: true // Post: this instance's date moved n days later. (Negative n // moves to an earlier date.) { fromJulian(toJulian() + n); } // Accessors public int getDay() // Pre: true // Post: returns the day from this instance, where // 1 <= getDay() <= #days in this instance's month { return day; } public int getMonth() // Pre: true // Post: returns the month from this instance's date, where // 1 <= getMonth() <= 12 { return month; } public int getYear() // Pre: true // Post: returns the year from this instance's date, where // getYear() != 0 { return year; } public int getWeekday() // Pre: true // Post: returns the day of the week upon which this instance // falls, where 0 <= getWeekday() <= 6; // 0 == Sunday, 1 == Monday, ..., 6 == Saturday { // calculate day of week return (toJulian() + 1)% 7; } public boolean equals(Day dd) // Pre: dd is a valid instance of Day // Post: returns true if and only if this instance and instance // dd denote the same calendar date { return (year == dd.getYear() && month == dd.getMonth() && day == dd.getDay()); } public int daysBetween(Day dd) // Pre: dd is a valid instance of Day // Post: returns the number of calendar days from the dd // instance's date to this instance's date, where // equals(dd.advance(n)) would hold { // implementation code return toJulian() - dd.toJulian(); } public String toString() // Pre: true // Post: returns this instance's date expressed in the format // "Day[year,month,day]" { // implementation code return "Day[" + year + "," + month + "," + day + "]"; } // Destructors -- None needed // Private Methods -- Mostly borrowed from _Core_Java_ /** * Computes the number of days between two dates * @return true iff this is a valid date */ private boolean isValid() { Day t = new Day(); t.fromJulian(this.toJulian()); return t.day == day && t.month == month && t.year == year; } private int toJulian() /** * @return The Julian day number that begins at noon of * this day * Positive year signifies A.D., negative year B.C. * Remember that the year after 1 B.C. was 1 A.D. * * A convenient reference point is that May 23, 1968 noon * is Julian day 2440000. * * Julian day 0 is a Monday. * * This algorithm is from Press et al., Numerical Recipes * in C, 2nd ed., Cambridge University Press 1992 */ { int jy = year; if (year < 0) jy++; int jm = month; if (month > 2) jm++; else { jy--; jm += 13; } int jul = (int) (java.lang.Math.floor(365.25 * jy) + java.lang.Math.floor(30.6001*jm) + day + 1720995.0); int IGREG = 15 + 31*(10+12*1582); // Gregorian Calendar adopted Oct. 15, 1582 if (day + 31 * (month + 12 * year) >= IGREG) // change over to Gregorian calendar { int ja = (int)(0.01 * jy); jul += 2 - ja + (int)(0.25 * ja); } return jul; } private void fromJulian(int j) /** * Converts a Julian day to a calendar date * @param j the Julian date * This algorithm is from Press et al., Numerical Recipes * in C, 2nd ed., Cambridge University Press 1992 */ { int ja = j; int JGREG = 2299161; /* the Julian date of the adoption of the Gregorian calendar */ if (j >= JGREG) /* cross-over to Gregorian Calendar produces this correction */ { int jalpha = (int)(((float)(j - 1867216) - 0.25) / 36524.25); ja += 1 + jalpha - (int)(0.25 * jalpha); } int jb = ja + 1524; int jc = (int)(6680.0 + ((float)(jb-2439870) - 122.1)/365.25); int jd = (int)(365 * jc + (0.25 * jc)); int je = (int)((jb - jd)/30.6001); day = jb - jd - (int)(30.6001 * je); month = je - 1; if (month > 12) month -= 12; year = jc - 4715; if (month > 2) year--; if (year <= 0) year--; } // Implementation Invariants: // year != 0 && 1 <= month <= 12 && 1 <= day <= #days in month // (year,month,day) not in gap formed by the change to the // modern (Gregorian) calendar private int year; private int month; private int day; }
The design and implementation of ADTs (i.e., classes) must be approached from two points of view simultaneously:
Client-supplier relationship:
________________ ________________ | | | | | Client |===USES===>| Supplier | |________________| |________________| (ADT user) (ADT)
The supplier's concerns include:
The clients' concerns include:
As we have noted previously, the interface of an ADT is the set of features (i.e., public operations) provided by a supplier to clients.
A precise description of a supplier's interface forms a contract between clients and supplier.
The client-supplier contract:
The contract
If we are both the clients and suppliers in a design situation, we should consciously attempt to separate the two different areas of concern, switching back and forth between our supplier and client "hats".
We can use the following design criteria for evaluating ADT (class) interfaces. Of course, some of these criteria conflict with one another; a designer must carefully balance the criteria to achieve a good interface design.
Some of the material here is based on the presentation in the following books:
The first version of these lecture notes were written for use in the first Java-based version of CSCI 211 (File Systems) during the fall semester of 1996. It was subsequently modified for use in the CSCI 581, Object-Oriented Design and Programming, classes in the fall of 1997 and spring of 1999.
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