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Usually, we start the presentations by introducing the speakers. You will all be familiar with Steve, a software engineer at Brock. I'm from Oita, a beautiful place that I love, and I think it’s great to be here.
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I know this is the standard in the community, but I don't think it adds much interaction to this presentation.
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The theme of my presentation at RubyKaigi Matsumoto is that I want to answer a question you must have.
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I’m excited to be here and to discuss what RBS is about.
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Social aspects are also significant. I visited both places about ten years ago and took some interesting photos.
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In Oita, the bus station has a special timetable, and we need a reservation to take the bus from there.
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In fact, social aspects are quite prominent, and the last one I want to mention is the community park.
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This will be a technical presentation; however, before diving into the presentation details, I would like to share some recent updates regarding RBS. The latest version is RBS 3.1 and 3.4, both of which were released last month.
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These updates introduce new syntaxes. Specifically, two new syntaxes were introduced in RBS3.0: a class module area syntax and the definition of areas for some long-named classes and modules.
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This corresponds to the way you assign a cross-module to some constant and use that as a class name or module name in your Ruby code.
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Another syntax is for importing classes from long package names, which is equivalent to import statements in Java and C#. However, this is specific to RBS and has no direct counterpart in Ruby.
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With RBS 3.0 and 3.4, some features have been improved. The RBS Assistant support now includes signature help and enhancements in RBS completion.
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When you type a parenthesis after a method call, signature help pops up automatically, displaying the documentation and types of the method parameters. You can input your method arguments in this interface.
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There's also an improvement in type name completion. For example, when you type "Chan," a list will pop up, and it resolves to the parsec token factory.
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Additionally, the system now inserts a shorter name based on the current module nesting context.
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However, a question arises: Why do we have two different type names for the same input? The parameter type is a fully qualified type name, while the return type uses a shorter name. Let's delve into this detail.
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When you are typing the parameter type in RBS, if the syntax is broken and the return type information is missing in the method definition, the current RBS parser stops working.
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The modular nesting context is lost, so this situation causes the parser to fall back to a backup mode and insert an approximate type name instead.
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Conversely, when typing the return type, it is syntactically correct. The parsing of the RBS file succeeds, and the module nesting context is computed, allowing the resolution of the shortest relative type names.
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This inconsistency arises from parsing errors. Moreover, we need a purpose that can continue working, even with syntax errors, to provide advanced IDE features like completion, signature help, and jump to definition.
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Let’s take a look at some examples in the video. In this RBS file, we define a class talk inside a conference. The outline view updates in real-time to reflect these changes.
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When we add attributes, like video, it immediately recognizes the attribute definition. You can continue defining attributes and see the navigation key update automatically.
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Once we close the class definition with `end`, there are no syntax errors remaining.
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Next, I will present how we can create a top-down password generator.
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This top-down password generator will emphasize error recovery. The target language is RBS, not Ruby, making it easier to focus on error recovery strategies.
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I developed this password generator to create top-down parses with error recovery features. The grammar is defined in WDSL, but currently, it doesn’t generate any code.
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Instead, it has an interpreter that receives the grammar definitions and parses the input.
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The grammar definition is specified using BNF notation, where we have terminal tokens like class keywords and method calls, as well as different non-terminals for module names and class members.
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In BNF notation, we will see how to repeat phrases or make them optional. This shows that the grammar supports zero or more class members.
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The backlog is primarily handled by method calls, representing class declarations, method definitions, or HTTP readers.
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The output of parsing is a concrete syntax tree rather than an abstract structure. Essentially, we create classes for each type of grammar definition, managing their relationships effectively.
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Let’s observe how the top-down parsing implementation will appear. For each non-terminal symbol, we have specific parsing methods. The cross member terminal must also be determined.
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The passing methods correspond to each rule body, validating the input against expected tokens and handling any discrepancies.
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For instance, if the first token in the input is a class declaration token, it will proceed accordingly; otherwise, it will check for method definitions or attribute declarations.
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The produced parsing result is a tree that includes various subtrees for different parsing elements, ensuring that class and method definitions are thoroughly represented.
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Let’s analyze another aspect of error recovery when it comes to flawed RBS files. If a method definition lacks a proper ending syntax, the parser may simply halt.
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For example, an RBS file missing colons will not yield usable results, even while it retains some structural elements.
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To address this, we want reliable error recovery. It’s not just about raising errors; we must also try to yield a useful structure even in the presence of issues.
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The first step in this approach will be to introduce a missing tree structure that indicates which token is expected.
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Considering our current context, you won’t typically gain the full method definition unless the parser encounters the appropriate tokens, leading to expected syntax.
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Let’s examine a case where it may conflict, such as when the parser sees a token that doesn’t match the expected syntax.
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In these circumstances, it is essential to establish whether we can bypass certain tokens instead of letting them obstruct overall parsing.
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Hence, if it’s sensible to delete tokens causing issues, we proceed accordingly and continue parsing.
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Identifying potential tokens in the input enhances our parsing logic. We can skip tokens that do not conform to the expected format.
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Let’s continue with the implementation of the parse to skip tokens that don’t align with the rules.
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After applying this, we can expect to find a workable outline allowing a jumps start to this processing.
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beyond that, we will come across instances where method definitions are correctly identified, even if they lack expected components and mark these scenarios effectively.
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This error recovery strategy mimics common approaches found in top-down parsing implementations, ensuring we meet code efficiency.
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In short, I’ll illustrate another aspect of RBS parsing. Looking at our current implementation, it seamlessly gathers new cross declarations without skipping a beat.
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On screen, shapes depict how parsing adapts to fresh details. You’ll observe that the framework captures changes, aptly reflecting any structural adjustments.
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The basic function retains major method definitions while highlighting their corresponding attributes in ability.
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However, let’s address how error recovery tends to differ across various implementation layers.
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As we venture deeper into scenarios where classes encounter method definitions, parsing focuses on elements present vs. those omitted.
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Potential modifications illustrate core changes to the class structure without impacting previous definitions.
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When defining a structure with multiple varieties at play, it’s critical to highlight the connection to the broader coding landscape.
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Backtrack to previous steps; we can resolve conflicts without additional parsing issues.
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We need a structured framework to facilitate this logic as we pursue deeper structural integrity.
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Overall, despite facing structural complexities, we design resilient parsing functions borne of sound grammatical backgrounds.
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In summary, you need strategic navigation through multifaceted grammars to maintain integrity.
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As we draw toward the conclusion, I want to emphasize the merits of evolving the mechanisms for RBS.
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Our focus centers on achieving excellent syntax completion and bolstering efficiency while making sense of complex inputs.
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As per user experience, enhancing usability remains paramount while scaffolding frameworks towards practical applications.
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Your feedback remains invaluable; we must continue evolving methodologies. I want to thank you for all your support.
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If there are any questions or comments, please feel free to reach out. I’m excited about the journey forward, keen to tackle challenges we face as a community.
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Having worked on these projects for around 15 years, I remain committed to driving forward the narratives surrounding RBS, types, and safety in programming.
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Exciting developments await us; let's make sure we stride towards them together!
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I'm eager to circle back with the abstracts I've mentioned and curious about future endeavors together.
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That’s a wrap on my part. Thank you once again for this opportunity and your ongoing engagement!
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Let’s make the best out of this, and ensure we keep striving for progress!
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Feel welcome to reach out anytime to discuss more about RBS or projects you want to explore together.
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For now, I’ll conclude my presentation. Best wishes to everyone as we invest in new chapters concerning our future!
