CSci 581: Obj.-Oriented Design & Programming
Spring Semester 1999
Lecture Notes


Data Abstraction

Maxim:
Simplicity is good; complexity is bad.

The most effective weapon that computing scientists have in their fight against complexity is abstraction. What is abstraction?

Abstraction:
concentrating on the essentials and ignoring the details.

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.

Procedural abstraction:
the separation of the logical properties of an action from the details of how the action is implemented.
Data abstraction:
the separation of the logical properties of data from the details of how the data are represented.

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.

Concrete Data Structures

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.

Abstract Data Structures

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.

Abstract Data Types

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?

Type:
a category of entities sharing common characteristics

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:

  1. a value (state) drawn from some set (domain) of possible values--in the case of INTEGER, a subset of the mathematical set of integers,

  2. a set of operations that can be applied to those values--in the case of 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 class construct provides a direct way to define ADTs in languages like C++ and Java.

Defining ADTs

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:

  1. the name of the ADT.
  2. the sets (or domains) upon which the ADT is built. These include the type being defined and the auxiliary types (e.g., primitive data types and other ADTs) used as parameters or return values of the operations.
  3. the signatures (syntax or structure) of the operations.
    • name
    • input sets (i.e., the types, number, and order of the parameters)
    • output set (i.e., the type of the return value)
  4. the semantics (or meaning) of the operations.

    There are two primary approaches for specifying the semantics of the operations:

    • The axiomatic (or algebraic) approach gives a set of logical rules (properties or axioms) that relate the operations to one another. The meaning of the operations are defined implicitly in terms of themselves.

    • The constructive (or abstract model) approach describes the meaning of the operations explicitly in terms of operations on other abstract data types. The underlying model may be any well-defined mathematical model or a previously defined ADT.

    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.

    Axiomatic Specification of an Unbounded Stack ADT

    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.

    Name

    Stack (of Item)

    In this specification, we are defining an ADT named 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

    The sets (domains) involved in the Stack ADT are the following:

    Stack:
    the set of all stack instances
    (This is the set we are defining with the ADT.)
    Item:
    the set of all items that can appear in a stack instance
    boolean:
    the primitive Boolean type { False, True }

    Signatures

    To specify the signatures for the operations, we use the notation for mathematical functions. By a tuple like (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 categorize the operations into one of four groups depending upon their functionality:

    • A constructor (sometimes called a creator, factory, or producer function) constructs and initializes an instance of the ADT.

    • A mutator (sometimes called a modifier, command, or "setter" function) returns the instance with its state changed.

    • An accessor (sometimes called an observer, query, or "getter" function) returns information from the state of an instance without changing the state.

    • A destructor destroys an instance of the ADT.
    We will normally list the operations in that order.

    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 Stack ADT operations are as follows.

    Constructors:

    create: -> Stack

    Mutators:

    push: (Stack, Item) -> Stack
    pop: Stack -> Stack

    Accessors:

    top: Stack -> Item
    empty: Stack -> boolean

    Destructors:

    destroy: Stack ->

    The operation 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.

    The separation of the traditional "pop" into two functions has two advantages:

    1. It results in an elegant, applicative stack specification whose operations fit cleanly into the mutator/accessor categorization.

    2. It results in a simpler, cleaner abstraction in which the set of operations is "atomic". No operation in the ADT's interface can be decomposed into other operations also in the interface.

    Also note that operation 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)

    We can specify the semantics of the Stack ADT with the following axioms. Each axiom must hold for all instances s of type Stack and all entities x of type Item.

    1. top(push(s,x)) = x
    2. pop(push(s,x)) = s
    3. empty(create()) = True
    4. empty(push(s,x)) = False

    The axioms are logical assertions that must always be true. Thus we can write Axioms 3 and 4 more simply as:

    1. empty(create())
    2. not empty(push(s,x))

    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 top(create()) and pop(create())?

    Clearly we do not want to allow either top or pop to be applied to an empty stack. That is, top and pop are undefined when their arguments are empty stacks.

    Functions may be either total or partial.

    • A total function A -> B is defined for all elements of A.

      For example, the multiplication operation on the set of real numbers R is a total function (R,R) -> R.

    • A partial function A -> B is undefined for one or more elements of A.

      For example, the division operation on the set of real numbers R is a partial function because it is undefined when the divisor is 0.

    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.

    Precondition of pop(Stack S):
    not empty(S)
    Precondition of top(Stack S)
    not empty(S)

    Note that we have not given the semantics of the destructor operation destroy. This operation cannot be handled in the simple framework we have established.

    Operation 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.

    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.

    Constructive Specification of a Bounded Stack ADT

    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.

    Name

    StackB (of Item)

    Sets

    In this specification of bounded stacks, we have one additional set involved, the set of integers.

    StackB:
    the set of all stack instances
    Item:
    set of all items that can appear in a stack instance
    boolean:
    the primitive Boolean type
    int:
    the primitive integer type { ..., -2, -1, 0, 1, 2, ... }

Signatures

In this specification of unbounded stacks, we define the create operation to take the maximum capacity as its parameter.

Constructors:

create: int -> StackB

Mutators:

push: (StackB, Item) -> StackB
pop: StackB -> StackB

In this specification, we add operation full to detect whether or not the stack instance has reached its maximum capacity.

Accessors:

top: StackB -> Item
empty: StackB -> boolean
full: StackB -> boolean

Destructors:

destroy: StackB ->

Semantics (Constructive Approach)

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.

create(int size) -> StackB S'
Precondition:
size >= 0
Postcondition:
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'
Precondition:
S is a valid StackB instance &&
not full(S)
Postcondition:
S' is a valid StackB instance &&
S' = S with I added as the new top.

pop(StackB S) -> StackB S'
Precondition:
S is a valid StackB instance &&
not empty(S)
Postcondition:
S' is a valid StackB instance &&
S' = S with the top item deleted

top(StackB S) -> Item I
Precondition:
S is a valid StackB instance &&
not empty(S)
Postcondition:
I = the top item on S
(S is not modified by this operation.)

empty(StackB S) -> boolean e
Precondition:
S is a valid StackB instance
Postcondition:
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
Precondition:
S is a valid StackB instance
Postcondition:
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) ->
Precondition:
S is a valid StackB instance
Postcondition:
StackB S no longer exists

Note that each operation except the constructor (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.

Also note that all of these 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.

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. (S and S' are implemented as different states of the same physical instance.)

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.

interface invariants:
invariants stated in terms of publically accessible features and abstract properties of the ADT instance.

implementation (representation) invariants:
detailed invariants giving the required relationships among the internal data fields of the implementation.

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.

Java Classes

A Java 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).

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 methods.

Class and Instance Methods

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.

Class and Instance Variables

In a similar fashion, the variables (data fields) declared in a class may be either class variables or instance variables.

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.

Public and Private Accessibility

The components of a class can be designated as public or private.

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.

Primitive or Reference Variables

A Java variable is a strongly typed "container" in memory that is declared to hold either:

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.

Implementing ADTs as Java Classes

One way to implement an ADT in Java is to do the following:

  1. Use the Java 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
        }
    

  2. Use an instance of the Java class to represent an instance of the ADT and, hence, variables of the class type to hold references to instances.

    For example, to declare a variable that can hold a reference to a StackB instance, we can use the following declaration:

        StackB stk;
    

  3. Represent the ADT's constructor by Java constructor methods.

    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.

  4. Represent the ADT operations by instance methods of the class. Thus the state of the ADT instance, which is given explicitly in the ADT signatures, becomes an implicit argument of all method calls. Mutators also have the state as an implicit return.

    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(); 
        }
    

  5. Make the constructors, mutators, accessors, and destructors public methods of the class. That is, precede the method's definition by the keyword public.

  6. Represent the ADT mutator operations by Java procedure (i.e., 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.

  7. As appropriate, implement some of the ADT mutator operations (e.g., a copy method) to return a new instance of the ADT's class rather than modify the instance itself (i.e., the implicit parameter).

  8. Represent the ADT accessor operations by Java function methods of the proper return type. These functions can access the encapsulated state of the class instance (which is the implicit argument of these methods) and compute a value to be returned.
        public boolean empty()
        {   //  code to implement operation
        }
    

  9. If necessary for deallocation of internal resources, represent the ADT destructor methods by explicit Java procedures; otherwise, just allow the automatic garbage collection to reclaim instances that are no longer being used.
        public void destroy()
        {   //  code to free resources
        }
    

  10. Use 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
        }
    

  11. Do not use 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.

  12. Include, as appropriate, 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.

  13. Add any other methods needed to make the ADT fit into the Java environment. For example, it is frequently useful to add a public 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.

Java Implementation of the Bounded Stack

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
}

A Date (Day) ADT

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.

Constructor

create(int y, int m, int d) -> Day D'
Precondition:
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
Postcondition:
D' is a valid new instance of Day with year y, month m, and day d

Mutators

setDay(Day D, int y, int m, int d) -> Day D'
Precondition:
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
Postcondition:
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'
Precondition:
D is a valid instance of Day
Postcondition:
D' is a valid instance of Day &&
D' = D with the date moved n days later (Negative n moves to an earlier date.)

Accessors

getDay(Day D) -> int d
Precondition:
D is a valid instance of Day
Postcondition:
d is day of the month from D, where 1 <= d <= #days in month getMonth(D)
(D is unchanged.)

getMonth(Day D) -> int m
Precondition:
D is a valid instance of Day
Postcondition:
m is the month from D, where 1 <= m <= 12
(D is unchanged.)

getYear(Day D) -> int y
Precondition:
D is a valid instance of Day
Postcondition:
y is the year from D, where y != 0
(D is unchanged.)

getWeekday(Day D) -> int wd
Precondition:
D is a valid instance of Day
Postcondition:
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
Precondition:
D and D' are valid instances of Day
Postcondition:
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
Precondition:
D and D' are valid instances of Day
Postcondition:
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
Precondition:
D is a valid instance of Day
Postcondition:
s is the date D expressed in the format "Day[getYear(D),getMonth(D),getDay(D)]".
(D is unchanged.)

Destructor

destroy(Day D) ->
Precondition:
D is a valid instance of Day
Postcondition:
D no longer exists

Java Class Implementation for Day

// 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; 
}

Client-Supplier Relationship

The design and implementation of ADTs (i.e., classes) must be approached from two points of view simultaneously:

supplier
the developers of the ADT -- the providers of the services.
client
the users of the ADT -- the users of the services (e.g., the designers of other ADTs).

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:

  1. gives the responsibilities of the client. These are the conditions under which the supplier must deliver results -- when the preconditions of the operations are satisfied (i.e., the operations are called correctly).
  2. gives the responsibilities of the supplier. These are the benefits the supplier must deliver -- make the postconditions hold at the end of the operation (i.e., the operations deliver the correct results).

The contract