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End-users can potentially style and customize websites by editing them through in-browser developer tools. Unfortunately, end-users lack the knowledge needed to translate high-level styling goals into low-level code edits. We present Stylette, a browser extension that enables users to change the style of websites by expressing goals in natural language. By interpreting the user’s goal with a large language model and extracting suggestions from our dataset of 1.7 million web components, Stylette generates a palette of CSS properties and values that the user can apply to reach their goal. A comparative study (N=40) showed that Stylette lowered the learning curve, helping participants perform styling changes 35% faster than those using developer tools. By presenting various alternatives for a single goal, the tool helped participants familiarize themselves with CSS through experimentation. Beyond CSS, our work can be expanded to help novices quickly grasp complex software or programming languages.
Kim et al. (Wed,) studied this question.
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