PTC-Lisp CoreAST: Essential Lisp Analyzer Infrastructure

Dec 8, 2025 by Admin 57 views

Hey guys, let's dive into something truly fundamental for our PTC-Lisp project: building the PTC-Lisp CoreAST type definitions and analysis infrastructure. This isn't just about writing code; it's about crafting the very backbone of our Lisp analyzer. Think of it as laying the concrete foundation for a skyscraper – if this part isn't rock-solid, everything we build on top of it will eventually crumble. Our goal here is ambitious yet focused: to create the initial, foundational infrastructure for the PTC-Lisp analyzer. This includes defining our CoreAST type definitions, sketching out the public API, and tackling the simplest but incredibly crucial transformations first, like handling literals and basic symbols. This work establishes the core structure, the very blueprint, for all subsequent analyzer development, ensuring we have a stable and well-defined base to grow from. We're talking about transitioning from raw parser output, which can be a bit messy, into a clean, structured, and easily digestible CoreAST that our future logic can confidently work with. This initial step might seem small, but it's monumental for the project's long-term success and maintainability. We're setting the stage for a powerful and reliable Lisp analysis engine, and trust me, getting these foundational pieces right now will save us countless headaches down the line. It's all about strategic, iterative development, making sure each layer is robust before moving to the next. So, let's roll up our sleeves and get this crucial phase locked down!

Laying the Groundwork: Why a CoreAST Matters

Alright, folks, let's talk about why creating a robust CoreAST (Core Abstract Syntax Tree) is absolutely essential for our PTC-Lisp analyzer. Imagine you're building a house. The parser gives us all the raw materials – the bricks, the wood, the wiring – but they're all just in a big pile. The CoreAST, on the other hand, is like having a meticulously organized blueprint and a set of standardized, pre-fabricated components. It takes the somewhat raw and unrefined output from our parser – what we call RawAST – and transforms it into a highly structured, semantically rich representation. This structured form is precisely what our analyzer needs to perform its complex tasks efficiently and accurately. Without a clearly defined CoreAST, every subsequent analysis step would have to constantly re-interpret the ambiguous RawAST, leading to brittle, hard-to-maintain, and error-prone code. We've laid out the architectural vision in our docs/ptc-lisp-analyze-plan.md, specifically sections 1-3, which serve as our guiding star for this entire process. This plan details the complete CoreAST structure and outlines our transformation approach, ensuring we have a unified vision. Our immediate dependency is the successful completion of the parser phase (issue #106 closed), meaning we now have reliable RawAST to work with. This isn't just about syntax anymore; it's about giving meaning to that syntax. The CoreAST is our intermediate representation that bridges the gap between the textual source code and the semantic understanding required for advanced analysis, optimization, and eventual execution. It's the moment where our Lisp code truly begins to take shape in a form that our system can understand and manipulate intelligently. This foundational work ensures that every piece of our Lisp Analyzer will speak the same language, making collaboration and future expansions much smoother. Seriously, guys, this is where we turn a pile of parts into a coherent, functional system.

Our Starting Point: The Current State of Affairs

So, where are we starting from, you ask? Well, as of now, our lib/ptc_runner/lisp/ directory already hosts the crucial parser infrastructure. We've got ast.ex, parser.ex, and parser_helpers.ex all working harmoniously to translate our PTC-Lisp code into what we call RawAST. This RawAST is delivered in the form of tagged tuples – things like {:symbol, :name} or {:ns_symbol, :ctx, :input}. It's functional, it works, and it gives us a starting point. However, and this is key, there's currently no CoreAST definition in place, nor do we have a dedicated Analyze module. This means while we can parse the code, we haven't yet given it the structured, semantically enriched form that our analyzer ultimately needs. The RawAST is, by design, a direct representation of the parsed tokens, which can sometimes be a bit verbose or contain structural elements that are more about parsing than about semantic analysis. Our ptc-lisp-analyze-plan.md meticulously specifies the complete CoreAST structure we're aiming for and details the exact transformation approach we'll use to get there. This plan acts as our comprehensive roadmap, ensuring that our Lisp Analyzer will have a robust and consistent internal representation. Our mission now is to bridge this gap: to take that raw parser output and elevate it into a CoreAST, a clean, standardized, and easily traversable tree that precisely reflects the program's structure and intent. This transformation isn't just a rename; it's a critical refinement step that simplifies all subsequent analysis stages. Think of it as moving from raw ingredients to finely chopped and prepped components ready for cooking. The RawAST is fantastic for what it does, but the CoreAST is what truly empowers our analyzer to understand, optimize, and eventually execute PTC-Lisp code with precision. We're essentially moving from 'what tokens are present' to 'what does this code mean structurally', making our analysis infrastructure significantly more powerful and manageable. This distinction is vital for any sophisticated language tool, and we're committed to doing it right for PTC-Lisp.

Building Blocks: Defining the CoreAST and Analyzer API

Alright, let's get into the heart of it: creating the foundational PTC-Lisp CoreAST type definitions and establishing our Lisp Analyzer's public API. First up, we're creating lib/ptc_runner/lisp/core_ast.ex. This file isn't just a place to dump some structs; it's where we meticulously define the type specifications for every single node in our CoreAST. Why are type specs so crucial in Elixir, you ask? Well, they act as both documentation and a safety net. They clearly articulate the expected structure of each CoreAST node, making our code self-documenting and easier for any developer (including future ourselves!) to understand. Tools like Dialyzer can then use these specs to catch potential type mismatches or bugs before our code even runs, giving us a significant boost in reliability and confidence. Each CoreAST node will be represented by a tagged tuple, strictly adhering to the plan outlined in our architectural document. For instance, a simple integer might transform from {:integer, 123} in RawAST to {:literal, 123} in CoreAST, or perhaps {:int, 123} depending on our final spec – the point is, it will be explicit and consistent. We're aiming for clarity and precision, ensuring that our CoreAST accurately reflects the program's structure in a way that’s optimal for analysis.

Next, we're rolling out lib/ptc_runner/lisp/analyze.ex. This module will house the public API skeleton for our Lisp Analyzer. The star of the show here is our analyze/1 function. This function serves as the single entry point for transforming any given RawAST element into its CoreAST counterpart. It's the gateway through which all our parsing output must pass before it can be truly understood by the system. A key pattern we're adopting, mirroring lib/ptc_runner/lisp/parser.ex, is the {:ok, result} | {:error, reason} return signature. This pattern is quintessential Elixir error handling: it explicitly communicates whether the analysis was successful and provides the CoreAST if it was, or a clear error_reason if something went wrong. This disciplined approach to error handling is vital for building robust and predictable systems. We don't want any silent failures; we want explicit success or explicit failure, always. This analysis infrastructure will make it straightforward to integrate our analyzer into other parts of the system, providing a clean and predictable interface. By defining these structures and the API up front, we're not just coding; we're engineering a reliable foundation for all the exciting features to come in our PTC-Lisp ecosystem. This includes ensuring that our PTC-Lisp CoreAST type definitions are unambiguous, making the life of any developer interacting with this module infinitely easier. We're talking about a high-quality, maintainable, and robust piece of software that will serve us well.

The First Transformations: Handling Literals and Symbols

Now that we've got our CoreAST definitions and API structure in place, it's time to tackle the very first, yet incredibly important, transformations for our Lisp Analyzer: handling literals and symbols. When we talk about literals, we're referring to the most basic, self-representing pieces of data in our language. Think about nil, true, false, integers (like 123), floating-point numbers (like 3.14), strings (like "hello world"), and keywords (like :my_key). These are the fundamental atoms of data. For this initial phase, the transformation of literals is relatively straightforward: they mostly pass through as they are, but within our CoreAST structure. For example, a RawAST integer like {:integer, 123} might become {:int_literal, 123} in CoreAST, providing a consistent tag for all literal types. While this might seem like a simple pass-through, it's absolutely crucial because it establishes the baseline for how all data values will be represented in our CoreAST, ensuring uniformity and ease of processing for later stages of the analysis infrastructure. Getting these basic elements right confirms our pipeline is functioning correctly and our type definitions are being applied as intended. It's like checking if the basic plumbing works before installing the fancy fixtures; simple but non-negotiable.

Next up, we're dealing with symbols. Symbols are a bit more nuanced because their meaning can change based on their context. In our PTC-Lisp CoreAST, we have a few key transformations for symbols:

Simple Symbols: If the parser gives us {:symbol, name}, our analyzer will transform this into {:var, name}. This explicitly marks it as a variable reference within our CoreAST, distinguishing it from other types of symbols. For instance, {:symbol, :filter} becomes {:var, :filter}. This clarity is vital for accurately tracking variable usage and scope in subsequent analysis phases.
Namespaced Symbols (Context): When we encounter {:ns_symbol, :ctx, key}, this signifies a reference to the execution context. Our analyzer transforms this into {:ctx, key}. This transformation is specifically designed to recognize and correctly tag values that are meant to be retrieved from the application's context, such as {:ns_symbol, :ctx, :input} becoming {:ctx, :input}. This is incredibly important for data flow analysis, as it tells us exactly where certain values are expected to originate from.
Namespaced Symbols (Memory): Similarly, {:ns_symbol, :memory, key} denotes a reference to a persistent memory store. This will transform into {:memory, key} in our CoreAST. An example would be {:ns_symbol, :memory, :results} becoming {:memory, :results}. This mechanism is crucial for operations that interact with a shared, mutable state, providing a clear indication of read/write operations on this memory.

What about unknown namespaced symbols? This is an interesting edge case! If we encounter {:ns_symbol, :something_else, key} where something_else isn't ctx or memory, we'll treat it as a regular variable. So, {:ns_symbol, :unknown, :value} would transform into {:var, :unknown__value} (or similar, depending on precise naming conventions for clarity, but the core idea is it becomes a generic variable). This provides a sensible default and prevents the analyzer from crashing on unexpected input while still allowing for future expansion of recognized namespaces. These precise PTC-Lisp CoreAST type definitions and transformations are the bedrock upon which our sophisticated Lisp Analyzer will be built, enabling it to accurately interpret and process our PTC-Lisp programs. Getting these basic parsing and analysis steps correct is non-negotiable for the long-term health and accuracy of our entire system. We're talking about making our code not just parsed, but understood at a fundamental level.

Embracing Complexity: Recursive Analysis of Collections

Now, let's talk about where our Lisp Analyzer really starts to flex its muscles: handling collections, specifically vectors and maps. These data structures are a cornerstone of Lisp and introduce a layer of complexity because they often contain other expressions, including other collections, creating nested structures. This is where the concept of recursive analysis becomes absolutely critical. Our analyzer needs to be smart enough to not just recognize a vector or a map, but to then delve into each of its elements and recursively apply the same analysis rules. This means that if you have a vector containing an integer, a symbol, and another nested vector, our analyzer must correctly transform all three elements into their respective CoreAST nodes before assembling the parent vector's CoreAST representation.

Consider vectors. A RawAST vector might look like {:vector, [elem1, elem2, elem3]}. Our PTC-Lisp CoreAST type definitions will specify a node like {:vector, [core_elem1, core_elem2, core_elem3]}. The key here is that core_elem1, core_elem2, and core_elem3 are already CoreAST nodes, meaning they've gone through the analyze/1 function themselves. This applies to both empty vectors ({:vector, []}) which simply become {:vector, []} in CoreAST, and vectors with elements, like {:vector, [1, {:symbol, :x}]} transforming into {:vector, [{:int_literal, 1}, {:var, :x}]}. The analyzer's job is to map over the list of elements within the vector and call itself on each one, collecting the results.

Similarly, for maps, the process is analogous but with an added twist. Maps in Lisp are typically represented as a sequence of key-value pairs. In RawAST, this might be {:map, [{key1, value1}, {key2, value2}]}. In our PTC-Lisp CoreAST, this will transform into something like {:map, [{core_key1, core_value1}, {core_key2, core_value2}]}. Again, core_key and core_value are themselves fully analyzed CoreAST nodes. The recursive nature means that if a key is a keyword and a value is a nested map, both will be correctly analyzed. An empty map {:map, []} would transform to {:map, []}. A more complex example might be {:map, [{{:keyword, :a}, 1}, {{:symbol, :b}, {:vector, [2, 3]}}]}. Our analysis infrastructure needs to handle this gracefully, transforming it into something like {:map, [{:keyword, :a}, {:int_literal, 1}}, {{:var, :b}, {:vector, [{:int_literal, 2}, {:int_literal, 3}]}]}. This recursive capability is what allows our Lisp Analyzer to understand complex program structures, making it powerful enough to handle real-world PTC-Lisp code. Without it, our analyzer would be limited to only flat data structures, which simply isn't enough for a functional programming language. It’s a foundational piece of logic that demonstrates the true power of our CoreAST approach.

The Nitty-Gritty: Implementation Hints and Best Practices

Alright team, let's get down to the brass tacks of implementing this Lisp Analyzer phase. We've got a clear path forward, and adhering to some best practices will make this process smoother and more robust. First off, we're creating three key files: lib/ptc_runner/lisp/core_ast.ex for our PTC-Lisp CoreAST type definitions, lib/ptc_runner/lisp/analyze.ex which will house our core analysis logic and API, and test/ptc_runner/lisp/analyze_test.exs for all our crucial unit tests. These files are the backbone of this current development push.

When it comes to patterns, we're going to stick to what works beautifully in Elixir. This means consistently using tagged tuples for all our CoreAST nodes. Why tagged tuples? Because they provide a clear, immutable, and pattern-matchable structure for our AST nodes, making it incredibly easy to process and transform them. For example, instead of just a raw list, we'll have {:vector, [element1, element2]}. We also need to closely follow the error handling patterns already established in lib/ptc_runner/lisp/parser.ex. This means that our analyze/1 function (and any helpers) should consistently return {:ok, result} upon success or {:error, reason} if something goes awry. This explicit error handling is a cornerstone of resilient Elixir applications and ensures that callers of our analysis infrastructure always know the outcome of an operation without resorting to exceptions.

Now, let's talk edge cases – these are the scenarios that often trip up less robust systems, but we're going to tackle them head-on. We need to explicitly consider:

Empty collections: Both [] (empty vector) and {} (empty map) should be handled correctly. An empty vector {:vector, []} should simply transform into {:vector, []} in our CoreAST. The same applies to an empty map {:map, []} becoming {:map, []}. While seemingly trivial, correctly handling these ensures our Lisp Analyzer doesn't fall over on basic, valid input.
Nested collections: This is where the recursive magic happens! Our analyzer must be capable of deeply nested structures like a vector containing a map, which in turn contains another vector. For example, {:vector, [1, {:map, [{{:keyword, :a}, {:vector, [2, 3]}}]}]} should be fully and correctly analyzed down to its deepest levels. This demonstrates the power and correctness of our recursive analysis logic and our PTC-Lisp CoreAST type definitions in action.
Unknown namespace symbols: As discussed earlier, if we encounter a namespaced symbol like {:ns_symbol, :some_unknown_space, :value} that isn't ctx or memory, we'll default to treating it as a regular variable reference. This means transforming it into {:var, :some_unknown_space__value} (or a similarly formatted {:var, ...}). This graceful fallback prevents crashes and offers a predictable behavior for currently unsupported namespaces, making our analysis infrastructure more resilient and forward-compatible. By diligently addressing these details, we're building a foundation that is not just functional, but also robust, predictable, and ready for future expansion, proving our commitment to high-quality software engineering.

Proving It Works: Our Test Plan

Alright, folks, coding is one thing, but proving that our PTC-Lisp CoreAST type definitions and Lisp Analyzer actually work as intended is paramount. That's where our comprehensive test plan comes in. We're going to lean heavily on unit tests for this phase, as they allow us to isolate and verify the correctness of each small piece of our analysis infrastructure. Unit tests are our first line of defense against bugs, ensuring that individual functions and transformations behave exactly as expected before we even think about combining them.

Here’s a breakdown of the specific unit tests we’ll be writing:

Literals Pass-Through: We'll confirm that nil, true, false, integers, and floats are correctly recognized and passed through to their CoreAST literal forms without alteration. For example, {:integer, 123} should yield {:int_literal, 123} (or whatever our specific CoreAST tag is).
Strings: A string like {:string, "hello"} must transform faithfully into {:string, "hello"} in CoreAST.
Keywords: {:keyword, :name} should correctly become {:keyword, :name} in CoreAST.
Simple Symbols: We'll test {:symbol, :filter} and verify it transforms into {:var, :filter}, confirming our variable representation.
Namespaced Symbols: This is crucial. We'll have tests for {:ns_symbol, :ctx, :input} transforming into {:ctx, :input} and {:ns_symbol, :memory, :results} transforming into {:memory, :results}. These ensure our specific namespace handling is correct. We'll also test the unknown namespace symbol edge case, verifying {:ns_symbol, :unknown, :key} defaults to {:var, :unknown__key}.
Empty Collections: Both {:vector, []} and {:map, []} should yield their identical CoreAST counterparts, {:vector, []} and {:map, []}, proving our handling of empty data structures.
Collections with Elements: We'll test {:vector, [1, 2]} to ensure it transforms into {:vector, [{:int_literal, 1}, {:int_literal, 2}]}. For maps, {:map, [{{:keyword, :a}, 1}]} should correctly become {:map, [{:keyword, :a}, {:int_literal, 1}]}. These tests confirm the recursive analysis for immediate elements.
Nested Collections: This is the ultimate test for our recursive logic. We'll craft scenarios involving vectors within maps, maps within vectors, and even deeply nested structures. For example, {:vector, [1, {:map, [{{:keyword, :b}, {:vector, [2, 3]}}]}]} will be tested to confirm every single element, no matter how deeply nested, is correctly analyzed into its CoreAST form. These tests are vital for ensuring the robustness of our Lisp Analyzer against real-world complex code structures.

Finally, we'll ensure mix compile --warnings-as-errors passes without a hitch. This enforces strict code quality and catches potential issues early, especially related to our PTC-Lisp CoreAST type definitions. And of course, existing tests must continue to pass, guaranteeing we haven't introduced any regressions. While an integration test (parse source -> analyze -> verify CoreAST structure) is optional for this phase, it's definitely something to consider in the future to validate the end-to-end pipeline. For now, a comprehensive suite of unit tests will provide us with the confidence that our foundational analysis infrastructure is solid and ready for the next stages of development.

What's Next? Understanding the Scope

Alright, team, while we're super excited about building out this foundational PTC-Lisp CoreAST type definitions and the initial Lisp Analyzer infrastructure, it's equally important to clearly define what's out of scope for this specific issue. This isn't because these items aren't important – quite the opposite! They are critical, but tackling everything at once would dilute our focus and make this foundational phase unnecessarily complex. We're embracing an iterative development approach, meaning we build a strong core first, and then incrementally add more advanced features. This strategy ensures our analysis infrastructure remains stable and manageable as we grow.

So, for this phase, we are explicitly not touching the following:

Special Forms: Things like let, if, fn, when, cond are fundamental to Lisp, but they introduce complex control flow and scope management that will be handled in a subsequent issue. Our current focus is on literal and symbol representation.
Threading Macros: Macros like -> (thread-first) and ->> (thread-last) are powerful syntactic sugar. Their transformation and analysis will be addressed in a later stage, as they involve more intricate AST rewriting.
Logic Operators: and and or also involve specific short-circuiting logic and will be part of a future expansion of our analyzer's capabilities.
Predicate Builders: Advanced constructs like where, all-of, any-of, and none-of are higher-order functions that require a deeper semantic understanding than our current foundational analysis infrastructure provides. They are definitely on the roadmap for later, more sophisticated analysis phases.
Tool Calls: The call special form, which will handle interactions with external tools or services, is a significant feature that requires its own dedicated development effort. This will come after our core language constructs are well-established.
Generic Function Calls: The transformation of {:list, [...]} into {:call, ...} for regular function invocations (where the first element of a list is the function to be called) is a crucial step for a Lisp Analyzer. However, this involves distinguishing between special forms and actual function calls, which adds a layer of complexity we are deferring for a follow-up issue, allowing us to focus purely on the PTC-Lisp CoreAST type definitions and basic node transformations first.
Pattern Analysis / Destructuring: Features like pattern matching and destructuring assignments are advanced syntactic and semantic concepts that will require a more mature analyzer. These are definitely future enhancements.
Integration with PtcRunner.Lisp.run/2: This is part of Phase 4 of our overall plan, focusing on execution. Our current work is purely on the analysis side; integration will happen once the analyzer is robust and complete.

By clearly defining these boundaries, we can maintain sharp focus on building a robust and reliable PTC-Lisp CoreAST and its initial analysis infrastructure. This phased approach ensures we deliver high-quality, working code at each step, paving the way for a powerful and complete Lisp Analyzer down the line.

In conclusion, guys, this phase of creating the PTC-Lisp CoreAST type definitions and analysis infrastructure is a critical step forward for our project. We're not just writing code; we're meticulously crafting the foundational elements that will empower our Lisp Analyzer to understand, optimize, and eventually execute PTC-Lisp code with precision. By focusing on a robust CoreAST, a clean API, and careful handling of literals, symbols, and collections, we're building a truly solid base. This strategic approach, coupled with comprehensive testing and a clear understanding of what's in and out of scope, ensures we're building a high-quality, maintainable, and scalable system. The future of PTC-Lisp is looking bright, and it all starts with these essential building blocks. Keep up the great work!