Framework Matters: Energy Efficiency of UI Automation Testing Frameworks

📅 2025-11-21
📈 Citations: 0
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🤖 AI Summary
This study investigates energy consumption disparities among Web UI automation testing frameworks to support green test design. In a controlled client-server environment, we conducted fine-grained power measurements using an external power meter, executing 35 repetitions each of common operations—page refresh, click, input, and scroll—with Puppeteer, Selenium, Nightwatch, and Cypress. Results reveal up to a sixfold difference in energy consumption across frameworks for identical operations: Puppeteer achieves the highest overall energy efficiency; Selenium excels in refresh and scroll operations; Nightwatch exhibits the highest energy overhead. This work presents the first systematic empirical characterization of energy expenditures of UI testing frameworks, introduces the concept of “energy transparency,” and provides evidence-based guidance for energy-aware framework selection. By quantifying the environmental impact of test automation, our findings advance sustainable software testing practices and inform eco-conscious development decisions.

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📝 Abstract
We examine per action energy consumption across four web user interface (UI) automation testing frameworks to determine whether consistent tendencies can guide energy-aware test design. Using a controlled client-server setup with external power metering, we repeat each UI action (refresh, click variants, checkbox, drag&drop, input-text, scroll) 35 times. Across each of the actions, energy costs vary by both framework and action. Puppeteer is the most efficient for left-click, right-click, double-click, checkbox, and input-text; Selenium is the most efficient for refresh and scroll; Nightwatch is generally the least energy efficient. The energy cost of performing the same action varied by up to a factor of six depending on the framework. This indicates that providing transparency of energy consumption for UI automation testing frameworks allows developers to make informed, energy-aware decisions when testing a specific UI action.
Problem

Research questions and friction points this paper is trying to address.

Comparing energy consumption across different UI automation testing frameworks
Identifying which frameworks are most efficient for specific UI actions
Providing transparency for developers to make energy-aware testing decisions
Innovation

Methods, ideas, or system contributions that make the work stand out.

Compares energy efficiency across UI testing frameworks
Measures per-action consumption via external power metering
Identifies optimal frameworks for specific UI actions
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