As we evolve the design of our domain-specific language (DSL) for MUD game development, it's important to consider the modularization of the language to manage complexity and scalability. In addition, to keep the system loosely coupled, we aim to build a flexible integration system where the language can operate on dynamic data structures without depending on external classes or rigid data formats. This paper explores how we can define a modular structure, handle dynamic data input via JSON, and access external data in a flexible manner, all while ensuring compatibility with FParsec for parsing.

1. Modularization: Create a way to organize code into modules or namespaces to promote reusability and structure.
2. Loose Integration: Build a dynamic integration system where data can be passed in, interpreted, and accessed by the language without strict dependencies on external types.
3. Data Handling via JSON: Allow data to be passed in as JSON, dynamically converted into structures that the language can work with.
4. Accessing External Data: Ensure that the DSL has a clean, dynamic way to access incoming data without the parser needing to know the shape of the data in advance.

Modularization is critical for organizing large projects and preventing name collisions. By allowing code to be grouped into modules or namespaces, we can give the language the ability to:

• Reuse functions and commands across different contexts.
• Define scoped variables and functions.
• Provide structure and organization for large codebases.

Modules will encapsulate variables, functions, and possibly other modules. Here's a basic syntax proposal:

    let <variable> = <expression>
    def <function_name>(<param1>, <param2>) -> <expression>

    let maxHealth = 100
    def attack(player, enemy) -> player.strength - enemy.defense

module Inventory:
    def pickUp(item) -> "Picked up " + item.name

In this example, we have two modules: Combat and Inventory. The Combat module defines a constant and a function for attacking, while Inventory defines a function to pick up items. These modules can be referenced independently, improving code organization.

To avoid name collisions, we may introduce a system where modules can be referenced via namespacing:

let message = Inventory.pickUp(sword)

In this example, we use namespacing to access functions from their respective modules.

The next challenge is how the language can interact with external data sources without hard dependencies on the data structure. To achieve this, the integration system will:

• Accept external data in a flexible format, such as JSON.
• Dynamically access and manipulate this data without requiring pre-defined structures.
• Keep the language parser and compiler agnostic to the shape of external data.

Rather than tightly coupling the language with specific external classes, we can design it to accept data as JSON and dynamically work with it. This approach allows the program written in the DSL to access arbitrary data structures.

We can define a syntax where the program can access JSON fields dynamically:

let health = data.player.health
let items = data.inventory.items

In this example, getContext() retrieves the external context (JSON), which the program can then access like any other variable. The program can read data fields from data (e.g., data.player.health or data.inventory.items).

To implement dynamic data handling in FParsec, we need a flexible parser that can accept arbitrary shapes of data and let the DSL interact with it. The following steps outline how we can accomplish this:

We can use a lightweight JSON parser to convert incoming JSON strings into F# data structures (e.g., Map<string, obj>). Once the JSON data is parsed, we can pass it to the DSL's runtime environment.

The AST will need to accommodate dynamic lookups on the parsed JSON data. For example, if we want to access data.player.health, the AST would need to support accessing fields from a dynamic object.

    | Literal of obj
    | Variable of string
    | BinaryOp of string * Expression * Expression
    | FunctionCall of string * Expression list
    | DynamicLookup of Expression * string   # New node type for dynamic lookups

Here, DynamicLookup is introduced as a new node type that allows accessing fields dynamically.

During interpretation, the DynamicLookup node can be evaluated by looking up fields in a Map<string, obj> that represents the incoming JSON data:

    match expr with
    | Literal v -> v
    | Variable v -> context.[v]
    | BinaryOp(op, left, right) -> (* Perform the binary operation *)
    | FunctionCall(name, args) -> (* Call a function *)
    | DynamicLookup(baseExpr, fieldName) ->
        let baseValue = eval baseExpr context
        match baseValue with
        | :? Map<string, obj> as map -> map.[fieldName]
        | _ -> failwith "Invalid dynamic lookup"

In this example, the DynamicLookup evaluates the base expression (baseExpr) and accesses the fieldName from the resulting value (which is assumed to be a map).

To summarize, this paper outlines a flexible approach to designing a modular, loosely integrated language for MUD development:

• Modularization provides structure and scalability through namespaces and modules.
• Loose Integration allows the language to dynamically interact with external data via JSON without creating hard dependencies.
• Dynamic Data Handling in the AST and runtime lets the language work with arbitrary data structures, ensuring flexibility.

This design creates a powerful yet flexible system for MUD game logic, supporting dynamic inputs and complex game behavior, all while keeping the language lightweight and extensible.