Energy Consumption Analysis of Programming Languages

Abstract

The escalating energy demands of modern computing infrastructure have made software-level energy efficiency a critical concern in the era of green computing. This paper presents a comprehensive empirical analysis of the energy consumption characteristics of four widely-used programming languages: Python, C++, Java, and JavaScript. Employing a controlled benchmarking framework, we evaluate each language across four canonical algorithmic tasks — Bubble Sort, Merge Sort, Fibonacci computation (both recursive and iterative), and Matrix Multiplication — using execution time, CPU utilization, memory usage, and estimated energy consumption as primary evaluation metrics. Our experimental results reveal that C++ consistently achieves the lowest energy footprint, consuming up to 22 times less energy than Python for computationally intensive operations. Java and JavaScript occupy an intermediate tier, offering a balance between execution efficiency and developer productivity. These findings provide empirically grounded guidance for software engineers, system architects, and researchers who seek to develop environmentally sustainable software systems. The study contributes to the growing body of knowledge in green software engineering and advocates for the inclusion of energy profiling as a first-class concern in software development practice.