Abstract
The responsiveness of web applications directly affects customer satisfaction and, as a consequence, business-critical metrics like revenue and conversion rates. However, building web applications with low response times is a challenging task. The heterogeneity of browsers and client devices as well as the complexity of today’s web applications lead to high development and test efforts. Measuring front-end performance requires a deep understanding of measurement tools and techniques as well as a lot of manual effort. With our approach, developers and designers can assess front-end performance for different scenarios without measuring. We use prediction models derived by a series of automated, systematic experiments to give early feedback about the expected performance. Our approach predicts the front-end performance of real-world web applications with an average error of 11% across all major browsers.
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Keywords
- Average Prediction Error
- Screen Design
- Performance Prediction Model
- Early Feedback
- Model Construction Process
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Westermann, D., Happe, J., Zdrahal, P., Moser, M., Reussner, R. (2013). Performance-Aware Design of Web Application Front-Ends. In: Daniel, F., Dolog, P., Li, Q. (eds) Web Engineering. ICWE 2013. Lecture Notes in Computer Science, vol 7977. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39200-9_13
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DOI: https://doi.org/10.1007/978-3-642-39200-9_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-39199-6
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