Font Feature File Checks: Beyond Simple Length
Hey everyone, let's chat about something that's been on my mind lately: the way we're checking for non-identical feature files in our font projects. Right now, the approach is a bit, well, naive. It mostly relies on just checking the file length. While this sounds simple and efficient, it's actually leading to some tricky situations, particularly a false negative we're seeing with NotoSansThai. This means we might be missing out on crucial differences because our current method is too basic to catch them. We really need to dig deeper here, guys. The goal is to ensure the integrity and accuracy of our font files, and a simple length check just isn't cutting it anymore. It's like trying to judge a book by its cover – you miss all the good stuff inside! So, we're going to explore why this happens and what we can do about it to make our checks more robust and reliable. This isn't just about fixing a bug; it's about establishing a better, more thorough process for font development.
The Pitfalls of Length-Based Checks
So, why is this naive check causing headaches, especially with fonts like NotoSansThai? It all boils down to the fact that two files can have the exact same file length but contain vastly different content. Think about it – you can add or remove spaces, change variable names, or even reorder certain lines of code, and the overall size of the file might not change. However, these subtle (or not-so-subtle) changes can have a significant impact on how the font's features behave. In the case of NotoSansThai, it seems like the ttx_diff tool, which is a pretty handy utility for comparing these files, is reporting a false negative. This means it's telling us the files are the same when, in reality, they're not. This is a big problem because it can lead to inconsistent font behavior across different platforms or versions, which is the last thing any of us want. We're aiming for consistency and reliability, and a check that misses these discrepancies is actually doing the opposite. It's like having a security guard who only checks if the door is locked, but doesn't bother to see if a window is wide open! We need to move past this rudimentary method and embrace a more intelligent way of comparing these critical font files. Our current system is essentially blind to any differences that don't manifest as a change in file size, and that's a pretty significant oversight when we're dealing with complex font data.
Why NotoSansThai is a Case Study
Let's dive a little deeper into why NotoSansThai is presenting such a clear example of this problem. When we look at the NotoSansThai font files, specifically the ones referenced in the designspace file (you can check it out here: https://github.com/notofonts/thai?f8f3f02470#sources/NotoSansThai.designspace), we're encountering a situation where the ttx_diff tool, using its default length comparison, incorrectly reports them as identical. This is a classic false negative. The tool sees the byte count is the same and throws a green light, but the underlying code or data within those files is different. What could be different, you ask? It could be anything from slightly altered glyph data, different substitution rules, or even just comments or whitespace variations that don't change the file size but alter the logic. For designers and developers, this is super frustrating because it means you can't rely on this basic check to catch potential issues. It gives you a false sense of security. Imagine you've made some crucial adjustments to a font's features, expecting them to be reflected, but because the file size is the same, your checking mechanism doesn't flag it. You might end up deploying a version of the font that doesn't behave as intended, leading to a cascade of problems down the line. This NotoSansThai example is a stark reminder that we need more sophisticated tools and methods to ensure file integrity. It highlights the limitations of simple size comparisons and pushes us to think about more intelligent ways to compare complex data structures like font feature files.
The Need for a Smarter Approach
Given the limitations of our current length-based comparison, it's clear we need a more smarter approach to verifying non-identical feature files. Relying solely on file size is like trying to identify a person by just counting their hairs – it's an incomplete picture! We need methods that can actually parse and understand the content of these files, not just their physical dimensions. This means moving towards techniques that can compare the meaning and structure of the feature code, rather than just its byte count. Think about it: even a single character difference in a feature file can drastically alter the typographic output of a font. A misplaced comma, an incorrect lookup index, or a slightly different anchor point can lead to rendering errors, unexpected ligatures, or broken substitutions. These are the kinds of subtle but critical differences that a simple length check will completely miss. We need to ensure that our checks are robust enough to catch these nuances, guaranteeing that every version of a font is behaving exactly as intended. This is crucial for maintaining consistency across different projects, platforms, and even for archival purposes. We want to be able to confidently say that our font files are exactly what they're supposed to be, without any hidden surprises lurking within their code. The future of font development demands more than just superficial checks; it requires a deep dive into the actual data.
Exploring Future Solutions
So, what does this smarter approach look like in practice? The ideal scenario, and something we should definitely strive for in the longer term, is to get our sources to use variable FEA (Feature File Association). Variable FEA allows for more dynamic and complex feature definitions within a single file, which can then be controlled by various parameters. If our source files are built with this advanced capability, it inherently makes comparisons more meaningful, as we're dealing with a more structured and often more optimized representation of the font's features. However, we all know that getting upstream sources to adopt new standards can be a long and winding road. So, barring the adoption of variable FEA across the board, we need to consider alternative, practical solutions. One promising avenue is a compile + merge approach. This would involve compiling the feature files into a more standardized intermediate format (like TrueType instructions or OpenType tables) and then comparing these compiled outputs. This way, we're comparing the actual behavior of the features, regardless of how the source code was written or formatted. Differences in whitespace, comments, or even minor variations in syntax would be normalized during the compilation process, leaving us with a comparison of the functional aspects of the feature code. This method would be significantly more reliable than a simple file length check and would help us catch those critical, subtle differences that currently slip through the cracks. It's about comparing apples to apples, or rather, comparing functional font features to functional font features!
Embracing a More Robust Comparison Strategy
Ultimately, the goal is to move away from superficial checks and embrace a more robust comparison strategy for non-identical feature files. The NotoSansThai example is a wake-up call, demonstrating that our current methods are insufficient. We need to build processes and utilize tools that can accurately distinguish between genuinely identical files and those that merely appear identical based on superficial metrics like file size. This isn't just about satisfying a code check; it's about ensuring the integrity and reliability of the fonts we produce and distribute. When we have confidence that our feature files are truly consistent or that any differences are intentional and well-understood, we reduce the risk of unexpected bugs, rendering issues, and compatibility problems. This robust strategy will ultimately save us time and resources by catching potential problems early in the development cycle, rather than discovering them later when they're much harder and more expensive to fix. It’s about being proactive, not reactive. We need to foster a culture where thoroughness is paramount, and where we don't cut corners on crucial validation steps. The long-term health and stability of our font projects depend on it, guys. Let's make sure we're building on a solid foundation of accurate and reliable file comparisons.
The Way Forward
As we move forward, the focus must be on implementing the smarter approaches we've discussed. Whether it's advocating for the adoption of variable FEA in upstream sources or developing and integrating a compile + merge workflow for our internal processes, the direction is clear: we need deeper, more meaningful comparisons. The current length-based check is simply not sufficient for the complexity and criticality of font feature files. We need to invest the time and resources into developing or adopting tools that can perform content-aware comparisons. This might involve using diffing algorithms that understand the structure of the font data or developing custom scripts that can parse and compare the compiled output of feature files. The key takeaway here is that accuracy and reliability should be the guiding principles. We owe it to ourselves and to the users of our fonts to ensure that the files we work with are precisely what they claim to be. Let's start the conversation about how we can best achieve this, perhaps by setting up a working group or by dedicating specific development cycles to tackle this important issue. By addressing this now, we can prevent future headaches and ensure the high quality of our font library. It's time to get serious about the details, because in the world of typography, the smallest differences can make the biggest impact.