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Antigravity Agent
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---
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id: wiki-2026-0508-dsl
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title: Domain-Specific Languages (DSL)
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category: 10_Wiki/Topics
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status: verified
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canonical_id: self
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aliases: [DSL, internal DSL, external DSL, fluent API, embedded DSL, NL-to-DSL]
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duplicate_of: none
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source_trust_level: A
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confidence_score: 0.9
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verification_status: applied
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tags: [dsl, programming-languages, abstraction, fluent-api, ddd, sql, regex, llm-dsl]
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raw_sources: []
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last_reinforced: 2026-05-10
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github_commit: pending
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tech_stack:
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language: any
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framework: ANTLR / PEG / Tree-sitter
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---
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# DSL (Domain-Specific Language)
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## 매 한 줄
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> **"매 specific domain 의 optimized 의 language"**. 매 SQL, regex, HTML, CSS 의 omnipresent. 매 internal (embedded) vs external. 매 modern: 매 LLM 의 NL → DSL 의 best interface. 매 IaC 의 Terraform / config DSL 의 boom.
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## 매 핵심
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### 매 type
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#### External DSL
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- 매 own grammar.
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- 매 parser / compiler 필요.
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- 예: SQL, regex, CSS, GraphQL, Gherkin, HCL (Terraform).
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#### Internal DSL (Embedded)
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- 매 host language 의 문법 안.
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- 매 fluent API.
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- 예: jQuery, RSpec, Gradle (Kotlin DSL), zod schema.
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### 매 design principle
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1. **Domain-aligned terminology**.
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2. **Declarative over imperative** ("what" not "how").
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3. **Composable**.
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4. **Readable by domain expert**.
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5. **Constrained** (less Turing-complete = better verification).
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### 매 famous DSL
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- **SQL**: 매 query.
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- **Regex**: 매 pattern.
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- **CSS**: 매 styling.
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- **HTML / JSX**: 매 markup.
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- **GraphQL**: 매 query.
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- **Cypher** (Neo4j): 매 graph.
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- **HCL** (Terraform): 매 IaC.
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- **Gherkin**: 매 BDD.
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- **Mermaid / PlantUML**: 매 diagram.
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- **dbt SQL**: 매 transformation.
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### 매 modern (LLM era)
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#### NL-to-DSL
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- 매 natural language → 매 SQL / regex / etc.
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- 매 GitHub Copilot regex helper.
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- 매 Text2SQL 의 mature.
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#### LLM-driven DSL
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- 매 LLM 의 better understand 매 specific DSL.
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- 매 internal company DSL 의 valuable.
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### 매 tooling
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- **ANTLR**: 매 parser generator.
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- **PEG.js / Peggy**: 매 PEG-based.
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- **Tree-sitter**: 매 modern incremental.
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- **Lark** (Python).
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- **MPS** (JetBrains): 매 projectional.
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### 매 응용
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1. **Configuration** (Helm, Terraform).
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2. **Workflow** (Airflow, GitHub Actions YAML).
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3. **Test specification** (Gherkin, RSpec).
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4. **Build** (Gradle, Bazel).
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5. **Domain modeling** (DDD ubiquitous language).
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6. **Hardware** (Verilog, VHDL).
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7. **Math / AI** (TLA+, Lean).
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## 💻 패턴
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### Internal DSL (TypeScript fluent)
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```ts
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// 매 query builder
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class QueryBuilder<T> {
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private filters: Filter[] = [];
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private sort: Sort[] = [];
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private limitN = 100;
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where(field: keyof T, op: Op, value: unknown): this {
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this.filters.push({ field, op, value });
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return this; // 매 chain
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}
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orderBy(field: keyof T, dir: 'asc' | 'desc'): this {
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this.sort.push({ field, dir });
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return this;
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}
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limit(n: number): this {
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this.limitN = n;
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return this;
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}
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build(): SQL {
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return `SELECT * FROM ${this.table} WHERE ${this.filters} ORDER BY ${this.sort} LIMIT ${this.limitN}`;
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}
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}
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// 매 use
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const query = new QueryBuilder<User>()
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.where('age', '>', 18)
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.where('country', '=', 'US')
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.orderBy('createdAt', 'desc')
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.limit(50);
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```
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### Zod schema (DSL-like)
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```ts
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import { z } from 'zod';
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const UserSchema = z.object({
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id: z.string().uuid(),
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email: z.string().email(),
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age: z.number().int().min(0).max(150),
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role: z.enum(['admin', 'user']),
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preferences: z.object({
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theme: z.enum(['light', 'dark']).default('light'),
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notifications: z.boolean().default(true),
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}).optional(),
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});
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type User = z.infer<typeof UserSchema>;
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```
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### External DSL (Lark in Python)
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```python
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from lark import Lark, Transformer
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grammar = """
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start: rule+
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rule: NAME ":" condition "→" action
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condition: "if" CNAME comparison NUMBER
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comparison: ">" | "<" | "=="
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action: CNAME "(" CNAME ")"
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NUMBER: /\\d+/
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%import common.CNAME
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%import common.NAME
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%import common.WS
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%ignore WS
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"""
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dsl = """
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high_score: if score > 90 → notify(student)
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warn: if attendance < 70 → email(student)
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"""
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parser = Lark(grammar)
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tree = parser.parse(dsl)
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class MyDSL(Transformer):
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def rule(self, items):
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name, cond, action = items
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return {'name': name, 'condition': cond, 'action': action}
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print(MyDSL().transform(tree))
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```
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### NL → SQL (LLM-driven)
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```python
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def nl_to_sql(query, schema):
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prompt = f"""You are a SQL expert.
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Schema:
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{schema}
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Convert this natural language to SQL:
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"{query}"
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Return ONLY the SQL, no explanation."""
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sql = llm.generate(prompt)
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# 매 validate
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if not is_safe(sql) or has_destructive(sql):
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raise ValueError('Unsafe SQL')
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return sql
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```
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### Gherkin (BDD)
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```gherkin
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Feature: User login
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Scenario: Successful login with valid credentials
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Given a registered user with email "test@example.com"
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And the user's password is "password123"
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When the user submits the login form
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Then they are redirected to "/dashboard"
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And a session cookie is set
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```
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```python
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from behave import given, when, then
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@given('a registered user with email "{email}"')
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def step_user(context, email):
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context.user = create_user(email)
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@when('the user submits the login form')
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def step_submit(context):
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context.response = client.post('/login', {...})
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@then('they are redirected to "{path}"')
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def step_redirect(context, path):
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assert context.response.url.endswith(path)
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```
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### Terraform HCL
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```hcl
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resource "aws_instance" "web" {
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ami = "ami-0c55b159cbfafe1f0"
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instance_type = var.environment == "prod" ? "t3.large" : "t3.micro"
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tags = merge(var.common_tags, {
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Name = "web-${var.environment}"
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})
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lifecycle {
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create_before_destroy = true
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prevent_destroy = var.environment == "prod"
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}
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}
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```
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### Custom config DSL (Python)
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```python
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class PipelineDSL:
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def __init__(self):
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self.steps = []
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def fetch(self, source: str):
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self.steps.append(('fetch', source))
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return self
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def transform(self, fn):
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self.steps.append(('transform', fn))
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return self
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def store(self, dest: str):
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self.steps.append(('store', dest))
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return self
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def run(self):
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# 매 execute
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...
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# 매 use
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pipeline = (PipelineDSL()
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.fetch('s3://my-bucket/data.csv')
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.transform(lambda df: df.dropna())
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.store('postgres://localhost/clean'))
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```
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### Tree-sitter (parse)
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```js
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const Parser = require('tree-sitter');
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const SQL = require('tree-sitter-sql');
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const parser = new Parser();
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parser.setLanguage(SQL);
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const tree = parser.parse('SELECT * FROM users WHERE id = 1');
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console.log(tree.rootNode.toString());
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```
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### Validate DSL (LLM-friendly)
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```python
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def validate_dsl(text, grammar):
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"""매 LLM 의 generated DSL 의 validate."""
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try:
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parser.parse(text)
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return {'valid': True}
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except ParseError as e:
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# 매 LLM 의 fix 의 ask
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fixed = llm.generate(f'Fix this DSL parse error:\n{e}\n{text}')
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return {'valid': False, 'fixed_attempt': fixed}
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```
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### DSL 의 evaluation
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```python
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class CompiledDSL:
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def __init__(self, ast):
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self.ast = ast
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def execute(self, context):
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return self._eval(self.ast, context)
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def _eval(self, node, ctx):
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if node.type == 'literal': return node.value
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if node.type == 'variable': return ctx[node.name]
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if node.type == 'binary_op':
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left = self._eval(node.left, ctx)
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right = self._eval(node.right, ctx)
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return apply_op(node.op, left, right)
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```
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## 매 결정 기준
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| 상황 | DSL Type |
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|---|---|
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| Domain expert reads | External DSL |
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| Programmer power | Internal (fluent) |
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| Configuration | YAML / HCL / TOML |
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| Build | Make / Gradle / Bazel |
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| Test BDD | Gherkin |
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| LLM interface | NL → DSL |
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| Constrained safety | External w/ verifier |
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**기본값**: 매 internal DSL (TypeScript / Python fluent) for code-heavy. 매 external for non-dev.
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## 🔗 Graph
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- 변형: [[External-DSL]] · [[Internal-DSL]] · [[Fluent-API]]
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- 응용: [[SQL]] · [[Terraform]] · [[Diagrams_as_Code]]
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- Adjacent: [[Bounded Contexts (DDD)]] · [[Domain-Driven-Design]] · [[Articulateness]] · [[Be-Detailed]] · [[Container_Queries]] (CSS DSL)
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## 🤖 LLM 활용
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**언제**: 매 internal API design. 매 NL-to-DSL system. 매 IaC. 매 BDD.
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**언제 X**: 매 simple imperative task.
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## ❌ 안티패턴
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- **DSL 의 Turing-complete 의 force**: 매 verification lose.
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- **No documentation / examples**: 매 adoption fail.
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- **Premature DSL** (small project): 매 over-engineering.
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- **NL → DSL 의 unvalidated**: 매 destructive (e.g., DROP TABLE).
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- **DSL leak host language**: 매 loose abstraction.
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## 🧪 검증 / 중복
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- Verified (Fowler "DSLs", PoEAA, ANTLR / Tree-sitter docs).
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- 신뢰도 A.
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- Related: [[Bounded Contexts (DDD)]] · [[Articulateness]] · [[Diagrams_as_Code]] · [[Custom-ESLint-Rules-Development]] · [[Be-Detailed]].
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## 🕓 Changelog
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| 날짜 | 변경 |
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|---|---|
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| 2026-05-08 | Phase 1 |
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| 2026-05-10 | Manual cleanup — internal/external + 매 zod / Lark / Gherkin / NL-to-SQL / Terraform code |
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