P342 - EnviroInfo 2023

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Konferenzbeitrag
Influence of Static Code Analysis on Energy Consumption of Software
(EnviroInfo 2023, 2023) Brosch, Christoph
In recent years, the rise of mobile devices, such as smartphones, smartwatches, or tablets, has led to an increased demand for energy-efficient software. In order to achieve this, developers can use static code analysis tools, such as Pylint, to detect potential issues in their code. This paper investigates how the usage of static code analysis influences the energy consumption of software. More specifically, we used the programming language Python and the general-purpose static code analysis tool Pylint [Py22]. For this purpose, we measured the energy consumption for algorithms implemented in the Benchmarks Game [Go22] before and after implementing the annotations and compared the results. Our findings suggest that resolving the annotations can have a negative impact on energy consumption. This was the case in 3 out of 8 algorithms. The remaining cases showed no significant difference. We assume that the increased energy consumption is due to the multitude of possibilities to implement annotations, leading to a possibility for worsening performance. Further research and experimentation are needed to objectively evaluate the impact of Pylint and static code analysis by extension, on energy consumption.