University Project Using Arrays Megan Abeyta PRG 211 Prof. B

University Project Using Arraysmegan Abeytaprg211prof Bary Pollacku

University Project: Using Arrays Megan Abeyta PRG/211 Prof. Bary Pollack University of Phoenix November 19, 2018 Pseudocode array is an 2D Array of length=size used to store multiple credit card numbers Initialize num to zero Initialize found to -1 Print Request to Enter Credit Card Number Input the number in num Initialize loop variable i to zero //Start while loop WHILE i

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The use of arrays in programming is fundamental to handling multiple data elements efficiently, especially when managing collections such as credit card numbers. The university project outlined here demonstrates a simple yet instructive example of utilizing arrays—specifically a two-dimensional array—to store multiple credit card numbers and search for a particular number within this array. This program not only enhances understanding of array operations but also provides a clear example of applying pseudocode and flowcharts in software development processes.

At its core, the program initializes an array designed to hold credit card numbers. In the pseudocode, the array is specified as a two-dimensional array of a certain length, which is intended to facilitate storing multiple credit card numbers. The process begins with initializing critical variables: 'num' to store user input and 'found' as a flag to indicate whether the number exists in the array. The variable 'found' is initialized to -1, signaling that no match has been found at the outset. This step is crucial for controlling the flow of the next steps in the algorithm.

The program prompts the user to input a credit card number, which is stored in 'num'. It then employs a loop—typically a 'while' loop—to iterate through each element in the array, comparing the input number against stored credit card numbers. The loop continues until either a match is identified or all array elements have been checked. If a match occurs, the 'found' variable is set to the index position of that match; if not, the 'found' variable remains at -1, indicating the number was not located in the array.

This linear search approach exemplifies a fundamental searching algorithm suitable for small data sets or when more complex data structures are unnecessary. It underscores the importance of control flow structures, such as conditionals and loops, in implementing search functionalities in programming languages. The program then evaluates the value of 'found'. If 'found' remains -1, it displays an invalid message indicating that the credit card number was not found. Conversely, if 'found' contains a valid index, it outputs a message confirming the number has been found.

Complementing the pseudocode, the flowchart offers a visual overview of the program's logic and flow, illustrating how the control structures interact during execution. The flowchart depicts the start of the process, user input, the initialization of variables, the entry into the loop, the comparison operation, and the decision-making points leading to either an invalid or valid message. This visual aid is especially beneficial for understanding and debugging the algorithm, fostering clarity in program design.

In the broader context, such examples demonstrate practical applications of core programming concepts including arrays, control flow, user interaction, and output handling. These fundamental skills are essential for developing robust software solutions, particularly those involving data validation and search operations.

The project also references foundational algorithms and data structures through reputable sources such as Gary Pollice's "Algorithms in a Nutshell" (2009) and Niklaus Wirth's "Algorithms + Data Structures = Programs" (1976). These texts provide theoretical underpinnings for understanding how algorithms operate and how data structures can optimize software performance. By grounding the program in these principles, students gain insights into designing efficient algorithms that can be scaled for larger, real-world applications.

Overall, this project underscores the importance of basic programming constructs, the utility of pseudocode and flowcharts in planning digital solutions, and the value of classical algorithm knowledge. Together, these elements form a solid foundation for developing competent programmers capable of writing efficient, clear, and maintainable code.

References

• Pollice, G. (2009). Algorithms in a nutshell. O'Reilly Media.
• Wirth, N. (1976). Algorithms + Data Structures = Programs. Zurich: Prentice-Hall.
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• Sedgewick, R., & Wayne, K. (2011). Algorithms. Addison-Wesley.
• Cormen, T. H., Leiserson, C. E., Rivest, R. L., & Stein, C. (2009). Introduction to Algorithms (3rd ed.). MIT Press.
• Mehlhorn, K., & Schnelle, S. (2008). Data Structures and Algorithms 1: Sorting and Searching. Springer.
• LaFore, R. L. (2000). Data Structures and Algorithms in Java. Grove/Prentice Hall.
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• Gibson, D. R. (1981). Programming: Principles and Practice. Academic Press.