A Domain Specific Language (DSL) is a computer language specialized for a particular application domain. Unlike a General Purpose Language (GPL) like C++, Python, or Java, which is designed to solve a wide variety of problems, a DSL is purposefully limited in scope. It trades broad applicability for targeted power, offering notation and abstractions that are highly expressive and productive within its niche.

Think of it as the difference between a fully-stocked workshop (a GPL) and a specialized tool like a torque wrench (a DSL). You can’t build a whole house with just a torque wrench, but for its specific job it is far safer, faster, and more effective than any general-purpose tool.

There are two main categories of DSLs:

• External DSLs: These are standalone languages with their own custom syntax, parser, and lexer. They don’t depend on another language to be interpreted. Classic examples are ubiquitous in computing:

  • SQL: For querying databases.
  • HTML/CSS: For structuring and styling web documents.
  • Regex: For defining text search patterns.
  • GLSL/HLSL: Shading languages for programming GPUs.

• Internal (or Embedded) DSLs: These are built inside a host GPL, using the features and syntax of the host language. Instead of writing a custom parser, you create a library of functions, types, and operators that, when combined, feel like a new language. This approach is especially popular in languages with powerful metaprogramming capabilities and flexible syntax.

The Power of Internal DSLs

Languages like LISP, Haskell, and Ruby are famous for being excellent “host” languages for internal DSLs. Their features: higher-order functions, custom operators, and macros; allow developers to craft APIs that are incredibly fluent and domain-specific.

Haskell, in particular, has a rich culture of DSL creation. Its strong, static type system allows developers to create DSLs where invalid programs are often impossible to even represent. This leads to extremely robust and safe domain models. A few famous examples from the Haskell ecosystem include:

• Parsec/Megaparsec: A library for building text parsers. You build complex parsers by combining smaller, simpler ones, creating a DSL for describing grammars.

• Aeson: A library for JSON serialization where the operators (.=, .:) form a mini-language for defining JSON object mappings.

• Pipes/Conduits: Libraries for streaming data that use custom operators to construct safe, efficient, and composable data-processing pipelines.

Successful DSLs in Industry

Beyond the academic and functional programming worlds, DSLs are a pragmatic tool used to solve real-world business problems.

• Ruby on Rails: The entire framework is a collection of brilliantly designed internal DSLs. ActiveRecord provides a DSL for database queries and migrations (has_many :posts), and the routing system provides a DSL for defining URL patterns (get '/patients/:id', to: 'patients#show'). This is a key reason for its reputation for high developer productivity.

• Terra: As mentioned in other documents, Terra is a low-level language that is itself a DSL embedded within Lua. It allows for LISP-like metaprogramming to generate high-performance C-like code at runtime, a powerful technique for just-in-time compilation and specialization.

• Build Systems (Make, Gradle, Rake): These are all DSLs for defining software build tasks and their dependencies. Gradle, for example, uses an internal DSL based on Groovy or Kotlin to create highly flexible and readable build scripts.

• Configuration DSLs (HCL): HashiCorp Configuration Language (HCL) is an external DSL used in tools like Terraform and Vault. It was designed to be a more human-readable and structured alternative to JSON or YAML for defining infrastructure as code.

Relevance to Ribbon

Ribbon’s design philosophy is highly influenced by the idea of empowering developers to create their own DSLs. A primary goal is to make DSL creation not an advanced, esoteric technique, but a common, everyday tool for solving problems.

Ribbon is designed to be a premier host language for internal DSLs, for both host-side and guest-side code. This is achieved through:

• A Toolkit-First Approach: Ribbon provides the fundamental, composable building blocks (allocators, effects, types) that make it easy to define the semantics of a new domain.

• Safety Across the Boundary: The core challenge of many DSLs, especially for untrusted guest code, is security. Ribbon’s type system, with its static tracking of memory regions (Algebraic Effects), allows a DSL author to provide powerful capabilities to end-users while statically proving that the code cannot escape its sandbox.

• Performance on Demand: A DSL written in Ribbon can be as high-level or as low-level as needed. For a trusted, internal DSL, you can compile it down to native machine code with zero overhead. For a public-facing modding API, you can compile it to a sandboxed Bytecode VM with runtime checks.

Ribbon aims to combine the metaprogramming flexibility of languages like LISP and Lua with the safety guarantees of languages like Haskell, while maintaining native performance. We are creating a powerful and secure foundation for building the next generation of domain-specific tools.