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springboot-tdd

Desarrollo guiado por pruebas para Spring Boot usando JUnit 5, Mockito, MockMvc, Testcontainers y JaCoCo. Úsalo al agregar funcionalidades, corregir errores o refactorizar.

¿Qué es springboot-tdd?

Esta habilidad proporciona una guía completa de desarrollo guiado por pruebas (TDD) para servicios Spring Boot, con el objetivo de alcanzar una cobertura superior al 80% combinando pruebas unitarias y de integración. Está diseñada para desarrolladores que trabajan con Spring Boot y necesitan un flujo de trabajo sistemático: escribir pruebas que fallen, implementar el código mínimo para pasarlas, refactorizar manteniendo las pruebas en verde y verificar la cobertura con JaCoCo. La habilidad cubre múltiples capas de prueba: unitarias con JUnit 5 y Mockito (siguiendo el patrón Arrange-Act-Assert), pruebas de capa web con MockMvc, pruebas de integración con @SpringBootTest, y pruebas de persistencia con @DataJpaTest y Testcontainers para entornos que imitan producción. También incluye configuraciones para JaCoCo en Maven/Gradle, recomendaciones de aserciones con AssertJ y constructores de datos de prueba. Es compatible con cualquier IDE que admita agentes de código. El flujo promueve pruebas rápidas, aisladas y deterministas, enfocándose en el comportamiento en lugar de los detalles de implementación.

Compatible con~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/springboot-tdd

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Documentación

Flujo de Trabajo TDD para Spring Boot

Guía de TDD para servicios Spring Boot con cobertura del 80%+ (unitaria + integración).

Cuándo Usarlo

  • Nuevas funcionalidades o endpoints
  • Corrección de errores o refactorizaciones
  • Agregar lógica de acceso a datos o reglas de seguridad

Flujo de Trabajo

  1. Escribe las pruebas primero (deben fallar)
  2. Implementa el código mínimo para que pasen
  3. Refactoriza con las pruebas en verde
  4. Verifica la cobertura (JaCoCo)

Pruebas Unitarias (JUnit 5 + Mockito)

@ExtendWith(MockitoExtension.class)
class MarketServiceTest {
  @Mock MarketRepository repo;
  @InjectMocks MarketService service;

  @Test
  void createsMarket() {
    CreateMarketRequest req = new CreateMarketRequest("name", "desc", Instant.now(), List.of("cat"));
    when(repo.save(any())).thenAnswer(inv -> inv.getArgument(0));

    Market result = service.create(req);

    assertThat(result.name()).isEqualTo("name");
    verify(repo).save(any());
  }
}

Patrones:

  • Arrange-Act-Assert
  • Evita mocks parciales; prefiere stubbing explícito
  • Usa @ParameterizedTest para variantes

Pruebas de Capa Web (MockMvc)

@WebMvcTest(MarketController.class)
class MarketControllerTest {
  @Autowired MockMvc mockMvc;
  @MockBean MarketService marketService;

  @Test
  void returnsMarkets() throws Exception {
    when(marketService.list(any())).thenReturn(Page.empty());

    mockMvc.perform(get("/api/markets"))
        .andExpect(status().isOk())
        .andExpect(jsonPath("$.content").isArray());
  }
}

Pruebas de Integración (SpringBootTest)

@SpringBootTest
@AutoConfigureMockMvc
@ActiveProfiles("test")
class MarketIntegrationTest {
  @Autowired MockMvc mockMvc;

  @Test
  void createsMarket() throws Exception {
    mockMvc.perform(post("/api/markets")
        .contentType(MediaType.APPLICATION_JSON)
        .content("""
          {"name":"Test","description":"Desc","endDate":"2030-01-01T00:00:00Z","categories":["general"]}
        """))
      .andExpect(status().isCreated());
  }
}

Pruebas de Persistencia (DataJpaTest)

@DataJpaTest
@AutoConfigureTestDatabase(replace = AutoConfigureTestDatabase.Replace.NONE)
@Import(TestContainersConfig.class)
class MarketRepositoryTest {
  @Autowired MarketRepository repo;

  @Test
  void savesAndFinds() {
    MarketEntity entity = new MarketEntity();
    entity.setName("Test");
    repo.save(entity);

    Optional<MarketEntity> found = repo.findByName("Test");
    assertThat(found).isPresent();
  }
}

Testcontainers

  • Usa contenedores reutilizables para Postgres/Redis para reflejar el entorno de producción
  • Conéctate mediante @DynamicPropertySource para inyectar URLs JDBC en el contexto de Spring

Cobertura (JaCoCo)

Fragmento de Maven:

<plugin>
  <groupId>org.jacoco</groupId>
  <artifactId>jacoco-maven-plugin</artifactId>
  <version>0.8.14</version>
  <executions>
    <execution>
      <goals><goal>prepare-agent</goal></goals>
    </execution>
    <execution>
      <id>report</id>
      <phase>verify</phase>
      <goals><goal>report</goal></goals>
    </execution>
  </executions>
</plugin>

Aserciones

  • Prefiere AssertJ (assertThat) por legibilidad
  • Para respuestas JSON, usa jsonPath
  • Para excepciones: assertThatThrownBy(...)

Constructores de Datos de Prueba

class MarketBuilder {
  private String name = "Test";
  MarketBuilder withName(String name) { this.name = name; return this; }
  Market build() { return new Market(null, name, MarketStatus.ACTIVE); }
}

Comandos de CI

  • Maven: mvn -T 4 test o mvn verify
  • Gradle: ./gradlew test jacocoTestReport

Recuerda: Mantén las pruebas rápidas, aisladas y deterministas. Prueba el comportamiento, no los detalles de implementación.

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/claude-api

Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.

affaan-m/everything-claude-code

End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.

affaan-m/everything-claude-code

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/everything-claude-code-conventions

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/frontend-design

Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.

affaan-m/gget

gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.

affaan-m/literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

affaan-m/motion-ui

Production-ready UI motion system for React/Next.js. Use when implementing animations, transitions, or motion patterns.

affaan-m/project-guidelines-example

Example project-specific skill template based on a real production application.

affaan-m/pubmed-database

Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.

affaan-m/scholar-evaluation

Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.

affaan-m/uspto-database

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

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