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Along the way we encounter all the jargon — classes, inheritance, instances, linkage, methods, objects, polymorphisms, and more — but we take it out of the realm of magic and see how it translates into the things we have known and done all along. To share this fun you need to be reasonably fluent in ANSI-C to begin with — feeling comfortable with structures, pointers, prototypes, and function pointers is a must. We start with a careful information hiding technique for abstract data types, add generic functions based on dynamic linkage and inherit code by judicious lengthening of structures.

Finally, we put it all together in a class hierarchy that makes code much easier to maintain. Programming takes discipline. Good programming takes a lot of discipline, a large number of principles, and standard, defensive ways of doing things right. Pro- grammers use tools.

Good programmers make tools to dispose of routine tasks once and for all. Object-oriented programming with ANSI-C requires a fair amount of immutable code — names may change but not the structures. Therefore, in chapter seven we build a small preprocessor to create the boilerplate required. It looks like yet another new object-oriented dialect language yanoodl perhaps? The following chapters refine our technology. In chapter eight we add dynamic type checking to catch our mistakes earlier on.

In chapter nine we arrange for automatic initialization to prevent another class of bugs. Chapter ten introduces delegates and shows how classes and callback functions cooperate to simplify, for example, the constant chore of producing standard main programs.

More chapters are concerned with plugging memory leaks by using class methods, storing and loading structured data with a coherent strategy, and disciplined error recovery through a system of nested exception handlers.

Finally, in the last chapter we leave the confines of ANSI-C and implement the obligatory mouse-operated calculator, first for curses and then for the X Window System. This example neatly demonstrates how elegantly we can design and implement using objects and classes, even if we have to cope with the idiosyn- crasies of foreign libraries and class hierarchies.

Each chapter has a summary where I try to give the more cursory reader a run- down on the happenings in the chapter and their importance for future work. Because we are building the techniques from scratch, I have refrained from making and using a massive class library, even though some examples could have benefited from it. An important part of this book is the enclosed source floppy — it has a DOS file system containing a single shell script to create all the sources arranged by chapter.

There is a ReadMe file — consult it before you say make. It is also quite instructive to use a program like diff and trace the evolution of the root classes and ooc reports through the later chapters. I have shown this to a number of people in courses and workshops and others have used the methods to get their jobs done. It would have stopped there as my footnote to a fad, if Brian Kernighan and my publishers, Hans-Joachim Niclas and John Wait, had not encouraged me to publish the notes and in due course to reinvent it all once more.

My thanks go to them and to all those who helped with and suffered through the evolution of this book.

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Last not least I thank my family — and no, object-orientation will not replace sliced bread. Hollage, October Axel-Tobias Schreiner 3. ANSI-C has int, double and char to name just a few.

A simple approach is to form aggregates such as arrays, structures, or unions. Pointers, according to C. What exactly is a data type?

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We can take several points of view. A data type is a set of values — char typically has distinct values, int has many more; both are evenly spaced and behave more or less like the natural numbers or integers of mathematics. Alternatively, we can define a data type as a set of values plus operations to work with them. Typically, the values are what a computer can represent, and the operations more or less reflect the available hardware instructions.

More complicated examples do not fare much better. Good programming principles dictate that we conceal the representation of a data item and declare only the possible manipulations.

At a theoretical level this requires us to specify the properties of the data type by mathematical axioms involving the possible operations. For example, we can remove an element from a queue only as often as we have added one previously, and we retrieve the elements in the same order in which they were added. Since the representation is not part of the definition, we are free to choose whatever is easi- est or most efficient to implement.

If we manage to distribute the necessary infor- mation correctly, use of the data type and our choice of implementation are totally independent. Abstract data types satisfy the good programming principles of information hid- ing and divide and conquer. Information such as the representation of data items is given only to the one with a need to know: With an abstract data type we cleanly separate the programming tasks of imple- mentation and usage: As an example we consider a set of elements with the operations add, find, and drop.

Viewed this way, set is an abstract data type. To declare what we can do with a set, we start a header file Set.

This technique of protecting header files is so standard, that the GNU C preprocessor recognizes it and does not even access such a file when its protecting symbol is defined. We can hardly reveal or assume less: Set will have to somehow represent the fact, that we are working with sets; add takes an element, adds it to a set, and returns whatever was added or already present in the set; find looks for an element in a set and returns whatever is present in the set or a null pointer; drop locates an element, removes it from a set, and returns whatever was removed; contains converts the result of find into a truth value.

If we used this name for a set function, we could no longer include stdio. On the one hand it makes it impossible to discover what a set looks like, but on the other hand it permits us to pass virtually anything to add and the other functions.

Not everything will behave like a set or an element — we are sacrificing type security in the interest of informa- tion hiding. However, we will see in chapter 8 that this approach can be made completely secure. Set is a pointer, not a type defined by typedef; therefore, we cannot define local or global variables of type Set.

Instead, we are only going to use pointers to refer to sets and ele- ments, and we declare source and sink of all data items in new. The text only shows the interesting parts of each new file, the source diskette contains the com- plete code of all examples. If they are, the descriptor has to indicate at least how much memory is required. This description leaves room for the functionality of strcmp: Real life objects need more functionality to do something useful.

For the moment, we restrict ourselves to the bare necessities for membership in a set. If we built a bigger class library, we would see that a set — and in fact everything else — is an object, too.

At this point, a lot of functionality results more or less for free. If all is well, we find the objects in the set and we should not find another new object. The program should simply print ok. The call to differ illustrates a semantic point: Similarly, once we remove the object, it should no longer be in the set.

Removing an element not in a set will result in a null pointer being passed to delete. For now, we stick with the semantics of free and require this to be acceptable. If an object stores no information and if every object belongs to at most one set, we can represent each object and each set as small, unique, positive integer values used as indices into an array heap[].

If an object is a member of a set, its array element con- tains the integer value representing the set. Objects, therefore, point to the set containing them. Sets and objects have the same representation, so new pays no attention to the type description. It only returns an element in heap[] with value zero: Before an object is added to a set, we let it contain the impossible index value MANY so that new cannot find it again and we still cannot mistake it as a member of any set.

A more realistic implementation should at least print a reasonable error message or use a general function for error handling which the user may overwrite. For our pur- pose of developing a coding technique, however, we prefer to keep the code uncluttered.

In chapter 13 we will look at a general technique for handling excep- tions. An element of heap[] is recycled by setting it to zero: A set is represented in its objects: If an ele- ment contains MANY, it can be added to the set, otherwise, it should already be in the set because we do not permit an object to belong to more than one set.

The other functions are just as simple. If so, we return it to object status by marking it with MANY: In this case, however, we would replicate most of the code of find in drop. Our implementation is quite unconventional. It turns out that we do not need differ to implement a set. We still need to provide it, because our application uses this function. We are done — for this solution we have not used the descriptors Set and Object but we have to define them to keep our C compiler happy: This time we use dynamic memory and represent sets and objects as structures: For an element, count records how many times this element has been added to the set.

If we decrement count each time the element is passed to drop and only remove the element once count is zero, we have a Bag, i. Since we will use dynamic memory to represent sets and objects, we need to initialize the descriptors Set and Object so that new can find out how much memory to reserve: If the reference count reaches zero, the element is removed from the set: The overhead of a function call is insignificant compared to the danger of an application being able to overwrite a critical value.

Our application in section 1. After it is dropped from the set once, contains will still find it in the bag. The test program now has the output ok drop? The application code can only access a header file where a descriptor pointer represents the data type and where operations on the data type are declared as functions accepting and returning generic pointers.

The descriptor pointer is passed to a general function new to obtain a pointer to a data item, and this pointer is passed to a general function delete to recycle the associated resources. Normally, each abstract data type is implemented in a single source file. Ideally, it has no access to the representation of other data types. If we continue to represent objects as small unique integer values, and if we put a ceiling on the number of objects available, we can represent a set as a bitmap stored in a long character string, where a bit selected by the object value is set or cleared depending on the presence of the object in the set.

A more general and more conventional solution represents a set as a linear list of nodes storing the addresses of objects in the set. This imposes no restriction on objects and permits a set to be implemented without knowing the representation of an object. For debugging it is very helpful to be able to look at individual objects.

Both functions return the number of characters written. For a new string we allocate a dynamic buffer to hold the text. When the string is deleted, we will have to reclaim the buffer. Based on the parameter, we could use a chain of if statements to handle each creation individually. The draw- back is that new would explicitly contain code for each data type which we sup- port.

It, too, must behave differently based on the type of the object being deleted: We could give delete another parameter: There is a much more general and elegant way: Part of each and every object will be a pointer with which we can locate a clean-up function.

We call such a function a destructor for the object. Now new has a problem. It is responsible for creating objects and returning pointers that can be passed to delete , i. The obvious approach is to make a pointer to the destructor part of the type descriptor which is passed to new.

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So far we need something like the following declarations: Initialization is part of the job of new and different types require different work — new may even require different arguments for different types: Since constructor and destructor are type-specific and do not change, we pass both to new as part of the type description. Note that constructor and destructor are not responsible for acquiring and releasing the memory for an object itself — this is the job of new and delete.

The constructor is called by new and is only responsible for initializing the memory area allocated by new. For a string, this does involve acquiring another piece of memory to store the text, but the space for struct String itself is allocated by new.

This space is later freed by delete. First, however, delete calls the des- tructor which essentially reverses the initialization done by the constructor before delete recycles the memory area allocated by new. Therefore, revising the declarations shown in section 2. What should this pointer point to? If all we have is the address of an object, this pointer gives us access to type-specific information for the object, such as its destructor function.

It seems likely that we will soon invent other type-specific functions such as a function to display objects, or our comparison function differ , or a function clone to create a complete copy of an object.

Therefore we will use a pointer to a table of function pointers. Looking closely, we realize that this table must be part of the type description passed to new , and the obvious solution is to let an object point to the entire type description: Looking down this list, we notice that every function works for the object through which it will be selected. Only the constructor may have to cope with a partially initialized memory area.

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We call these functions methods for the objects. Calling a method is termed a message and we have marked the receiving object of the message with the parameter name self. Since we are using plain C functions, self need not be the first parameter. Many objects will share the same type descriptor, i. We call all objects with the same type descriptor a class; a single object is called an instance of the class.

So far a class, an abstract data type, and a set of possible values together with operations, i. An object is an instance of a class, i. Conventionally speaking, an object is a value of a particular data type. The constructor is called by new for a new memory area which is mostly uninitialized: This is why we initialize this pointer already in new: The object is created at run time and the dashed pointers are then inserted.

We force a conversion of p which treats the beginning of the object as a pointer to a struct Class and set the argument class as the value of this pointer.

Next, if a constructor is part of the type description, we call it and return its result as the result of new , i. Section 2. Note that only explicitly visible functions like new can have a variable parame- ter list. Since we might later want to share the original parameters among several functions, we pass the address of ap to the constructor — when it returns, ap will point to the first argument not consumed by the constructor. This is used to call the destructor if any exists.

Here, self plays the role of p in the previous picture. We force the conversion using a local variable cp and very carefully thread our way from self to its description: If the constructor decides to cheat, the destructor thus has a chance to correct things, see section 2. If an object does not want to be deleted, its destructor would return a null pointer. All other methods stored in the type description are called in a similar fashion. In each case we have a single receiving object self and we need to route the method call through its descriptor: For the moment at least, we guard against null pointers.

In any case, differ illustrates why this technique of calling functions is called dynamic linkage or late binding: We will call differ a selector function. It is an example of a polymorphic func- tion, i.

Once we implement more classes which all contain. We can view selectors as methods which themselves are not dynamically linked but still behave like polymorphic functions because they let dynamically linked functions do their real work. Polymorphic functions are actually built into many programming languages, e. This phenomenon is called overloading: There is no clear distinction here: Methods can be polymorphic without having dynamic linkage.

As an example, consider a function sizeOf which returns the size of any object: Notice the difference: They are derived from the correspond- ing components of struct Class by simply removing one indirection from the declarator. Here is the application: We show the size of a String object — not the size of the text controlled by the object — and we check that two different texts result in different strings. Finally, we check that a copy is equal but not identical to its original and we delete the strings again.

Dynamic linkage helps to clearly identify which functions need to be written to implement a new data type. The constructor retrieves the text passed to new and stores a dynamic copy in the struct String which was allocated by new: The destructor frees the dynamic memory controlled by the string.

Since delete can only call the destructor if self is not null, we do not need to check things: This can easily be done by calling new: If we really compare two distinct strings, we try strcmp: All these methods are static because they should only be called through new , delete , or the selectors.

The methods are made available to the selectors by way of the type descriptor: In order to properly initialize the type descriptor, it also includes the private header new. An atom is a unique string object; if two atoms contain the same strings, they are identical. Atoms are very cheap to compare: Atoms are more expensive to construct and destroy: Before the con- structor saves a text it first looks through the list to see if the same text is already stored.

Otherwise we insert the new string object into the circular list and set its reference count to 1. Book description programming infree ebook of c the tips blog download.

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