Optimizing Heap Sort for Repeated Values: A Modified Approach to Improve Efficiency in Duplicate-Heavy Data Sets

Sorting algorithms are critical to various computer science applications, including database management, big data analytics, and real-time systems. While Heap Sort is a widely used comparison-based sorting algorithm, its efficiency significantly diminishes when dealing with data sets containing a high volume of duplicate values. To address this limitation, this paper introduces a modified Heap Sort algorithm optimized for duplicate-heavy data. The proposed modification detects and handles duplicate values more efficiently by reducing unnecessary comparisons and swaps at the root of the heap and restructuring the heap more strategically. Experimental results demonstrate that the modified Heap Sort achieves up to a 15% reduction in sorting time, a 30% decrease in the number of swaps, and a 10% reduction in comparisons when tested on data sets with varying levels of duplication. These improvements highlight the enhanced computational efficiency and scalability of the modified algorithm in duplicate-heavy data scenarios. This advancement offers significant potential for improving sorting performance in practical domains such as big data analytics, database operations, and real-time data processing.