Energy Optimization in Software Development: A Comparative Study of Sorting Techniques

Abstract

The escalating levels of greenhouse gas emissions are attributable to human activities that fueled a pressing need to address energy consumption across various sectors, particularly in the realm of software development. This article explores the imperative of energy efficiency within the context of Green Software development, emphasizing its significance in mitigating environmental impact. Focusing on the comparative analysis of two widely-used sorting algorithms, Bubble Sort and Quick Sort, those study investigates their energy efficiency when handling large numerical datasets. The methodology encompasses meticulous steps, including application selection, data generation, power measurement, energy consumption analysis, and report generation. Through rigorous experimentation and analysis, the research article elucidates the energy consumption patterns of the sorting algorithms, providing insights into optimizing energy usage in software development. The findings underscore the importance of developing energy-efficient software systems, aligning with principles of environmental sustainability and responsible technological innovation.