I explored using ChatGPT's Code Interpreter to analyze browser compatibility data from the BCD project. My goal was to determine the latest released versions of different browsers. While the initial results weren't perfect, through a few iterations of feedback, the Code Interpreter generated a Python script that accurately extracted the desired information. I was impressed by the speed and efficiency of this process, as it accomplished in minutes what would have taken me much longer manually. The generated code also provided a starting point for further analysis, like visualizing browser release timelines. Despite minor imperfections, the Code Interpreter proved to be a powerful tool for quickly extracting and analyzing data.
I explored using LLMs for checking web API browser compatibility. Existing LLMs struggle with outdated data, so I experimented with MDN's Browser Compat Data (BCD). Initial trials using raw BCD JSON with GPT-4 had limitations. To improve this, I converted the BCD into English descriptions of API support and loaded it into a Polymath instance. This allows natural language queries about API compatibility across browsers, like "Is CSS Grid supported in Safari, Firefox, and Chrome?" or "When was CSS acos available in Chrome?". The results are promising, but further refinement is needed to ensure accuracy and reliability.
I've added a new feature to time-to-stable that lists experimental APIs across browsers using BCD. This helps developers track experimental APIs, understand their stability, and consider the implications for website integration. It helps answer questions about cross-browser compatibility and potential deprecation, informing decisions about using these APIs.
This post explores browser compatibility data, focusing on features present in some browsers but not others. I've created a tool, "Not yet Stable," to visualize these differences and help developers understand the current web platform landscape. While high-level comparisons are interesting, the real value lies in identifying smaller, unexpected compatibility issues that can cause frustration. The tool allows for granular comparisons between specific browsers (e.g., Chrome vs. Firefox, Safari vs. Firefox) to pinpoint these inconsistencies. I've observed significant discrepancies in media-related features, such as Web Codecs API, Picture-in-Picture, and MediaStreams. The goal is to leverage this data for better understanding and ultimately improve web compatibility.
I've created a tool called "Now Stable" using Browser Compat Data (BCD) to help developers determine when web APIs become stable across different browsers. This addresses the challenge of keeping up with browser updates and helps developers confidently choose APIs for their projects. The tool allows users to select their target browsers (e.g., Chrome, Safari, Firefox) and see a chronological list of when APIs became available across those browsers. I'm looking for feedback on how this tool can be improved and how developers would use this data.
Web compatibility is a major developer concern. While projects like Compat 2021 aim to address these issues, data-driven analysis is crucial for understanding the web's evolving compatibility landscape. This post highlights Browser Compat Data (BCD), a valuable resource from Mozilla that offers detailed compatibility information for web APIs. BCD bridges the gap between raw Web Platform Tests data and user-friendly tools like caniuse.com. I've created a demo app, "The Web Of...", utilizing BCD to visualize API availability across different browsers at specific points in time. This data empowers developers to make informed decisions about API usage, assess compatibility across browser engines, and track the overall progress of web compatibility. The availability of such data opens up possibilities for new metrics like a "CompatIndex" to quantify web compatibility. Contributions to the BCD project are encouraged to further enhance this valuable resource.