Impact of Extensions on Browser Performance: An Empirical Study on Google Chrome
Tags: machinelearning, ai, beginners, datascience
Published: 2024-04-12 16:36:32

*This is a Plain English Papers summary of a research paper called [Impact of Extensions on Browser Performance: An Empirical Study on Google Chrome](https://aimodels.fyi/papers/arxiv/impact-extensions-browser-performance-empirical-study-google). If you like these kinds of analysis, you should subscribe to the [AImodels.fyi newsletter](https://aimodels.substack.com) or follow me on [Twitter](https://twitter.com/mikeyoung44).*

## Overview

- Examines the impact of browser extensions on the performance of Google Chrome
- Measures metrics like energy consumption, response time, and CPU usage to analyze the performance impact
- Compares the performance of Chrome with and without extensions installed

## Plain English Explanation

This paper investigates how browser extensions can affect the performance of the Google Chrome web browser. <a href="https://aimodels.fyi/papers/arxiv/influence-gameplay-duration-hand-tracking-controller-based">Browser extensions</a> are additional software programs that users can install to add new features or customize their browsing experience. The researchers wanted to understand how these extensions impact important aspects of browser performance, such as energy consumption, response time, and CPU usage.

They conducted experiments by measuring these performance metrics for Chrome both with and without various extensions installed. This allowed them to see the direct impact that extensions can have on the overall performance of the browser. The findings from this study can help users make more informed choices about which extensions to install, and can also guide browser developers in designing more efficient extension systems.

## Technical Explanation

The researchers designed experiments to measure the performance impact of browser extensions on Google Chrome. They installed a variety of common extensions and recorded metrics like energy consumption, response time, and CPU usage. These measurements were compared to a baseline of Chrome running without any extensions.

The results showed that extensions can have a significant effect on browser performance. Some extensions caused substantial increases in energy usage and response times, while others had minimal impact. The CPU usage patterns also varied, with some extensions causing spikes in CPU utilization. The researchers analyzed these findings to understand the mechanisms by which extensions influence Chrome's performance.

<a href="https://aimodels.fyi/papers/arxiv/petshop-dataset-finding-causes-performance-issues-across">The study provides insights</a> into the tradeoffs users face when deciding which extensions to install, as well as guidance for browser developers on designing more efficient extension systems that minimize performance degradation.

## Critical Analysis

The paper provides a thorough and well-designed experiment to measure the impact of browser extensions on Chrome's performance. However, the researchers acknowledge that their study is limited to a specific set of popular extensions. The performance impact may vary for less common or more specialized extensions.

Additionally, the paper does not delve into the root causes of the performance differences observed. Further research could investigate the underlying architectural and implementation details that lead to varying levels of performance impact from different types of extensions.

<a href="https://aimodels.fyi/papers/arxiv/lessons-from-formally-verified-deployed-software-systems">While the study focuses on Chrome</a>, the findings may have implications for other browser platforms as well. Examining the performance effects of extensions across multiple browsers could yield valuable comparative insights.

## Conclusion

This empirical study on the impact of browser extensions on Google Chrome's performance provides valuable insights for both users and browser developers. The results demonstrate that the choice of extensions can significantly affect key metrics like energy consumption, response time, and CPU usage.

<a href="https://aimodels.fyi/papers/arxiv/navigating-post-api-dilemma-or-search-engine">These findings can help users make more informed decisions</a> about which extensions to install, balancing the desired features with the potential performance trade-offs. For browser vendors, the study highlights the need to design more efficient extension systems that minimize the performance impact on the overall browsing experience.

<a href="https://aimodels.fyi/papers/arxiv/mobile-user-experience-from-lens-project-based">As web browsers continue to be a central part of our digital lives</a>, understanding and optimizing the performance impact of extensions is an important area of research that can have far-reaching implications for both users and the broader technology ecosystem.

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