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2024 | OriginalPaper | Buchkapitel

Enhanced Bubble Sorting Visualizer with Sound

verfasst von : Shubham Tiwari, Neha Gupta, Devendra Chouhan, Ishwarlal Rathod, Harsh Vaja

Erschienen in: Global Economic Revolutions: Big Data Governance and Business Analytics for Sustainability

Verlag: Springer Nature Switzerland

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Abstract

In this research paper we are proposing a sorting visualizer with sound is a tool that can assist users in comprehending and learning about different sorting algorithms. It enables them to see in real-time the process of sorting a set of data, such as a list of numbers. The visualizer animates the movement of the data as the algorithm sorts it, making it easy to see how the algorithm works and how the order of the data changes. Sound effects, such as beeps or chimes, can also help the user understand the sorting process by providing an auditory cue for the algorithm’s various actions. When the algorithm compares two elements, for example, a beep may be heard, or a chime may be heard when elements are swapped. Sorting visualizers with sound can be used for educational purposes, such as teaching students about different sorting algorithms and how they work. They can also be used by programmers to better understand how specific sorting algorithms work, and to compare the efficiency of different algorithms. Additionally, sorting visualizers can be used to debug sorting code, and to ensure that the algorithm is sorting the data correctly. Overall, sorting visualizers with sound is a powerful tool for understanding, learning, teaching and debugging sorting algorithms. It offers a visual and auditory representation of the algorithm’s behavior, making it easy for users to understand the process and identify any errors. This tool can be used to improve understanding of sorting algorithms and to help developers write efficient code.

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Metadaten
Titel
Enhanced Bubble Sorting Visualizer with Sound
verfasst von
Shubham Tiwari
Neha Gupta
Devendra Chouhan
Ishwarlal Rathod
Harsh Vaja
Copyright-Jahr
2024
DOI
https://doi.org/10.1007/978-3-031-50518-8_6

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