 Alright, welcome. My name is Nico Riecke and I'll be presenting about checking your project for non-inclusive language. I was raised to be open to everyone except them as they are, but later in life I found that this is not enough. Because often there are hostile structures in society that are hostile to certain kinds of certain people. And one of those structures is language. So it's important to check your project for the presence of non-inclusive language so you can improve it. But you are aware of this issue already as Git changed the branch name from master to main. That's one example. But there are much more examples. And now I'm not a native English speaker. I'm Dutch. Which means that I look for expert information to see if I can prove some things. And looking for expertise I found the Inclusive Naming Initiative under the Linux Foundation. Which is a great community which also has a Slack channel you can join. They are very welcoming. And they have an open process to evaluate words that might be considered non-inclusive and determine if this is the case, why this is the case. And they recommend alternatives and also prioritize them with a tiered list to see what are the most things that need, are urgent to replace and what might be more like a suggestion to replace. So this is one source for expertise. Another I found is by the University of Washington. Which is a very extensive guide with many words. And it starts with an introduction about writing plain non-collegial language. Which is a good read to explain why this is important. Now, I work at an open source program office. And even if I were to check this on the dozens of projects we have open source, that will take quite a bit of time. If I would do that on our internal projects without talking about thousands, this would be an immense amount of work. So I need automation. Looking for automation, I want a tool that can discover words that are considered non-inclusive to explain why this is an issue. Especially if teams start using this tooling. I really want to suggest alternatives so they can take direct action and prioritize whether they need to focus on what is lesser of a priority. And maybe even correct it automatically if that is possible. Looking for tooling, first I thought maybe I can write something myself using regular expression. How hard can it be? Or maybe repurposing spell checkers like C-Spell. And finally I found Woke, which is a dedicated tool for this purpose. But thanks to Chris Ward who reached out to me yesterday. There's another tool I became aware of now just that. Veil, which is able to do much more like checking for grammar and spelling and also issues like non-inclusive language. So maybe that might have been a better use, but I went with Woke. Woke was developed by Caitlin Elfring at her time at the Render Runway and she introduced it in a blog post. It's really great that she did this with the motivation to get it out to as many people as possible. And Woke is a command line tool you can use to check your project. And as you can see down there there's a file that contains the word white list. This is considered non-inclusive. And so it highlights it, explains why this might be insensitive, suggests alternatives, and also has a level, in this case warning. So it's very explicit and actionable. And once everything is fine, according to the rules, then it says so. And all this is backed by rules that determine what terms to look for, what are the alternatives, and a node to instruct the user. Also, there's the option for categories to filter out. So you have a long list of rules within your organization or your project. Maybe say, okay, I only want to check for these types of rules. Looking to implement this, I saw the need to expand on the quite limited rule set that is built into Woke. I want to add more words, languages, Dutch, for example. I want to add jargon. I work in the energy sector. We have specific words that are far too complicated to include in documentation. And a lot of this is also subjective. Words matter more than others. So it needs to be configurable. And that brought me to build the Woke config builder, as I named it. This is a repository you can find to take and make your own. It's a hierarchical structure of rules that is composed and rendered out to a single Woke configuration file. And you can make your modifications, add things, and render out. Publish that somewhere. And then you can directly import that public URL in Woke for usage. Also, it has some ignore file definitions. So it doesn't check if you have dependency specified somewhere with a name that might trigger sort of a false positive that is also ignored. These are some of the categories started there. So you see a reference to the inclusive naming initiative definitions. You see some about the languages and all the various types of non inclusive boards. So you can actually filter them. Now, this is what I want you to take home. So please take a picture. If you want to take something from this talk, these are the resources that help me along the way and can help you. And please also check fail as an alternative to Woke. And please set aside somewhere 30 minutes like next week or the week after in your schedule to work on this, take a project, a project you like, and start checking it because then you have to read up on words that are non inclusive. You can go through whatever project you want to check. And this will be a very learning exercise, whether you do this manually or automatically to really get your head around why this is important, how to act on that. Thank you. Yeah, I don't have time for questions. Yeah. Yeah, the slides are already online. Yeah, yeah. So you can check it there. That's good point. Then you don't need to take a picture of only you can account or it once you go scrolling to your academy. Yeah, indeed, language matters. Yeah, I learned that. And especially if you go through the list like the University of Washington list, including naming initiative list, you see the words and why they matter. It's all explained. Yeah, you learn a lot, even just reading that material. All right, thank you.