Measuring time to interactivity for modern Web pages
Author(s)
Nathan, Vikram
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Other Contributors
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Hari Balakrishnan.
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Web pages continually strive for faster loading times to improve user experience. However, a good metric for "page load time" is elusive. In particular, we contend that modern web pages should be evaluated with respect to interactivity: a page should be considered loaded when the user can fully interact with all visible content. However, existing metrics fail to accurately measure interactivity. On one hand, "page load time", the most widely used metric, overestimates the time to full interactivity by requiring that all content on a page has been both fetched and evaluated, including content below-the-fold that is not immediately visible to the user. Newer metrics like Above-the-Fold Time and Speed Index solve this problem by focusing primarily on above-the-fold content; however, these metrics only evaluate the time at which a page is fully visible to the user, disregarding page functionality, and thus interactivity. In this thesis, we define a new metric called Ready Index, which explicitly captures interactivity. Defining the metric is straightforward, but measuring it is not, since web developers do not explicitly annotate the parts of a page that support user interaction. To solve this problem, we introduce Vesper, a tool which rewrites a page's source code to automatically discover the page's interactive state. Armed with Vesper, we compare Ready Index to prior load time metrics like Speed Index. We find that, across a variety of network conditions, prior metrics underestimate or overestimate the true load time for a page by between 24% and 64%. Additionally, we introduce a tool that optimizes a page for Ready Index and is able to decrease the median time to page interactivity by between 29% and 32%.
Description
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018. Cataloged from PDF version of thesis. Includes bibliographical references (pages 53-56).
Date issued
2018Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer SciencePublisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.