**Topic :**Programming in C/C++

**Author :**Alexander Allain

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the function. One way you could make the function would be to accept a pointer to an array. Another way would be to write a function that can take any number of arguments. So you could write avg(4, 12.2, 23.3, 33.3, 12.1); or you could write avg(2, 2.3, 34.4); Some library functions can accept a variable list of arguments (such as the venerable printf).

To use a function with variable number of arguments, or more precisely, a function without a set number of arguments, you would use the stdarg.h header file. There are four parts needed: va_list, which stores the list of arguments, va_start, which initializes the list, va_arg, which returns the next argument in the list, and va_end, which cleans up the variable argument list. Whenever a function is declared to have an indeterminate number of arguments, in place of the last argument you should place an ellipsis (which looks like '...'), so, int a_function(int x, ...); would tell the compiler the function should accept however many arguments that the programmer uses, as long as it is equal to at least one, the one being the first, x.

va_list is like any other variable. For example, va_list a_list;

va_start is a macro which accepts two arguments, a va_list and the name of the variable that directly precedes the ellipsis (...). So, in the function a_function, to initialize a_list with va_start, you would write va_start(a_list, x);

va_arg takes a va_list and a variable type, and returns the next argument in the list in the form of whatever variable type it is told. It then moves down the list to the next argument. For example, va_arg(a_list, double) will return the next argument, assuming it exists, in the form of a double. The next time it is called, it will return the argument following the last returned number, if one exists.

To show how each of the parts works, take an example function:

#include <stdarg.h>

#include <iostream.h>

double average(int num, ...)

{

va_list arguments; //A place to store the list of arguments

va_start(arguments, num); //Initializing arguments to store all values

int sum=0; // passed in after num

for(int x=0; x<num; x++) //Loop until all numbers are added

sum+=va_arg(arguments, double); //Adds the next value in argument list to sum.

va_end(arguments); //Cleans up the list

return sum/(double)num; //Returns some number (typecast prevents trunctation)

}

int main()

{

cout<<average(3, 12.2, 22.3, 4.5)<<endl;

cout<<saverage(5, 3.3, 2.2, 1.1, 5.5, 3.3)<<endl;

return 0;

}

It isn't necessarily a good idea to use a variable argument list at all times, because the potential exists for assuming a value is of one type, while it is in fact another, such as a NULL pointer being assumed to be an integer. Consequently, variable argument lists should be used sparingly.

**Lesson 18: Binary Trees: Part 1**

The binary tree is a fundamental data structure used in computer science. The binary tree is a useful data structure for rapidly storing sorted data and rapidly retrieving stored data. A binary tree is composed of parent nodes, or leaves, each of which stores data and also links to up to two other child nodes (leaves) which can be visualized spatially as below the first node with one placed to the left and with one placed to the right. It is the relationship between the leaves linked to and the linking leaf, also known as the parent node, which makes the binary tree such an efficient data structure. It is the leaf on the left which has a lesser key value (ie, the value used to search for a leaf in the tree), and it is the leaf on the right which has an equal or greater key value. As a result, the leaves on the farthest left of the tree have the lowest values, whereas the leaves on the right of the tree have the greatest values. More importantly, as each leaf connects to two other leaves, it is the beginning of a new, smaller, binary tree. Due to this nature, it is possible to easily access and insert data in a binary tree using search and insert functions recursively called on successive leaves.

The typical graphical representation of a binary tree is essentially that of an upside down tree. It begins with a root node, which contains the original key value. The root node has two child nodes; each child node might have its own child nodes. Ideally, the tree would be structured so that it is a perfectly balanced tree, with each node having the same number of child nodes to its left and to its right. A perfectly balanced tree allows for the fastest average insertion of data or retrieval of data. The worst case scenario is a tree in which each node only has one child node, so it becomes as if it were a linked list in terms of speed. The typical representation of a binary tree looks like the following:

10

/ \

6 14

/ \ / \

5 8 11 18

The node storing the 10, represented here merely as 10, is the root node, linking to the left and right child nodes, with the left node storing a lower value than the parent node, and the node on the right storing a greater value than the parent node. Notice that if one removed the root node and the right child nodes, that the node storing the value 6 would be the equivalent a new, smaller, binary tree.

The structure of a binary tree makes the insertion and search functions simple to implement using recursion. In fact, the two insertion and search functions are also both very similar. To insert data into a binary tree involves a function searching for an unused node in the proper position in the tree in which to insert the key value. The insert function is generally a recursive function that continues moving down the levels of a binary tree until there is an unused leaf in a position which follows the rules of placing nodes. The rules are that a lower value should be to the left of the node, and a greater or equal value should be to the right. Following the rules, an insert function should check each node to see if it is empty, if so, it would insert the data to be stored along with the key value (in most implementations, an empty node will simply be a NULL pointer from a parent node, so the function would also have to create the node). If the node is filled already, the insert function should check to see if the key value to be inserted is less than the key value of the current node, and if so, the insert function should be recursively called on the left child node, or if the key value to be inserted is greater than or equal to the key value of the current node the insert functin should be recursively called on the right child node. The search function works along a similar fashion. It should check to see if the key value of the current node is the value to be searched. If not, it should check to see if the value to be searched for is less than the value of the node, in which case it should be recursively called on the left child node, or if it is greater than the value of the node, it should be recursively called on the right child node. Of course, it is also necessary to check to ensure that the left or right child node actually exists before calling the function on the node.

Because binary trees have log (base 2) n layers, the average search time for a binary tree is log (base 2) n. To fill an entire binary tree, sorted, takes roughly log (base 2) n * n. Lets take a look at the necessary code for a simple implementation of a binary tree. First, it is necessary to have a struct, or class, defined as a node.

struct node

{

int key_value;

node *left;

node *right;

};

The struct has the ability to store the key_value and contains the two child nodes which define the node as part of a tree. In fact, the node itself is very similar to the node in a linked list. A basic knowledge of the code for a linked list will be very helpful in understanding the techniques of binary trees. Essentially, pointers are necessary to allow the arbitrary creation of new nodes in the tree.

It is most logical to create a binary tree class to encapsulate the workings of the

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