Understanding Quality of Experiences on Different Mobile Browsers: Measurements, Analysis, and Implications
November 30, 2017 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Yun Ma, Shuailiang Dong
arXiv ID
1711.11521
Category
cs.SE: Software Engineering
Cross-listed
cs.PF
Citations
3
Venue
arXiv.org
Last Checked
4 months ago
Abstract
The web browser is one of the major channels to access the Internet on mobile devices. Based on the smartphone usage logs from millions of real-world Android users, it is interesting to find that about 38% users have more than one browser on their devices. However, it is unclear whether the quality of browsing experiences are different when visiting the same webpage on different browsers. In this paper, we collect 3-week consecutive traces of 337 popular webpages on three popular mobile browsers: Chrome, Firefox, and Opera. We first use a list of metrics and conduct an empirical study to measure the differences of these metrics on different browsers. Then, we explore the variety of loading time and cache performance of different browsers when visiting the same webpage, which has a great impact on the browsing experience. Furthermore, we try to find which metrics have significant effect on the differences, investigating the possible causes. Finally, according to our findings, we give some recommendations to web developers, browser vendors, and end users.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Software Engineering
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Microservices: yesterday, today, and tomorrow
π
π
The Cartographer
A Survey of Machine Learning for Big Code and Naturalness
R.I.P.
π»
Ghosted
An Overview on Smart Contracts: Challenges, Advances and Platforms
R.I.P.
π»
Ghosted
Slither: A Static Analysis Framework For Smart Contracts
R.I.P.
π»
Ghosted
ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted