This project refers to an Arduino library implementing a generic, dynamic stack (array version).

The data structure is implemented as a class in C++.

For more information, you can get the project itself ‘StackArray‘.

This project refers to an Arduino library implementing a generic, dynamic stack (array version).

The data structure is implemented as a class in C++.

For more information, you can get the project itself ‘StackArray‘.

To calculate a prefix expression, we either convert a number from ASCII to decimal (in the loop ‘while’ at the end of the program) or implement the operation indicated by the first character of the expressions to the two terms, with a recursive calculation. This function is recursive, but it uses a global array containing the expression and an index number for the current character of the expression. The index number goes beyond each sub-expression calculated.

The following program demonstrates a significant processing operation on arrays of strings. More precisely, we present the re-sorting of a set of strings in order to classify them. So, we read the strings and place them in a temporary storage area (buffer) large enough to be able to store all, keeping in an array a pointer to each string. Then we re-sort the pointers (only pointers and not strings to increase the performance) to place the pointer to the “smallest” string at the first position of the array, the pointer to the next “largest” string at the second position of the array, and so on.

The following program reads a set of edges that define an undirected graph and creates a representation of this graph with an adjacency matrix, giving a[i][j] and a[j][i] the value of 1 if there is an edge from i to j or from j to i in the graph, or the value of 0 if it does not exist. Also, we assume that the number of vertices V is a constant known at compilation time. Otherwise, there should be dynamic memory allocation for the array that represents the adjacency matrix.

The following program finds all the occurrences of a word in a text string. We set the text string as an array of characters of fixed size (although we could, instead, use the operator ‘new’) and read it from the standard input using the function cin.get(). The memory allocation for the word entered in the command line and passed on as argument is done by the system before this program is called and we find the pointer to the string in argv[1]. For every starting position i in the array a, tries to associate the substring starting from this position with the p, checking character by character for equality. Each time we reach the end of p successfully, we display the starting position (i) of the word in the text on the screen.

This program demonstrates the use of an array and is representative of the usual situation in which we store data in one array to process them later. It counts the number of pairs of N randomly generated points of the unit square, which can be connected to a line segment of length less than ‘d’, using the point data type. Because the execution time of this program is O(n^{2}), it can’t be used for large N.

The aim of this program is to assign to a[i] the value 1 if i is a prime number and the value 0 if not. Initially, all elements of the array take the value 1 to indicate that there are no numbers which are known not to be prime. Then all elements of the array corresponding to indexes that are known not to be primes (multiples of known primes) take the value 0. If a[i] has the value 1 even after all multiples of smaller primes have taken the value 0, we know that i is a prime number.

The program generally simulates a Bernoulli trials sequence, a familiar and abstract notion of probability theory. So, if you flip a coin N times, we expect “head” to occur N/2 times – but it could occur anything between 0 and N times. The program performs the experiment M times, reading the N and M from the command line. It uses an array ‘f’ to count the frequency with which the result “i heads” appears for 0 <= i <= N, and then displays a histogram of the results of experiments with an asterisk for every 10 appearances. Also, the operation behind the program – of indexing an array with a calculated value – is critical to the effectiveness of many computational procedures.

**Sequential Search.**

This algorithm checks whether the number ‘v’ is contained in a set of numbers already stored in the data a[0], a[1], …, a[r-1] of the array ‘a’ (where ‘r’ the number of elements in it), comparing it sequentially with all numbers, starting from the beginning. If the check reaches the end without finding the number, the value -1 is returned. Otherwise, we are returned the index of the position of the one-dimensional array containing the number.

This project refers to an Arduino library implementing a generic, dynamic queue (array version).

The data structure is implemented as a class in C++.

For more information, you can get the project itself ‘QueueArray‘.

If we replace the loops ‘for’ of the simple version of weighted quick-union (you’ll find it in a previous article) with the following code, we reduce the length of each route passing to the half. The end result of this change is that after a long sequence of operations the trees end up almost level.

This program reads from the standard input a sequence of pairs of non-negative integers which are less than N (interpreting the pair [p q] as a “link of the object p to object q”) and displays the pairs that represent those objects which are not yet connected. The program complies with the array ‘id’ to include an entry for each object and applies that id[q] and id[p] are equal if and only if p and q are connected.

If we replace the body of the while loop of the quick-find algorithm (you can find it in a previous article) with the following code we have a program that meets the same specifications as the quick-find algorithm but performs fewer calculations for the act of union, to the expense of more calculations for act of finding. The ‘for’ loop and the ‘if’ operation that follows in this code determine the necessary and sufficient conditions in the array ‘id’ that p and q be linked. The act of union is implemented by the assignment id[i] = j.

This program is a modification of the simple quick-union algorithm (you’ll find it in a previous article). It uses an extra array ‘sz’ to store the number of nodes for each object with id[i] == i in the corresponding “tree”, so the act of union to be able to connect the smaller of the two specified “trees” with the largest, and thus avoid the formation of large paths in “trees”.