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Spring Boot 驗證迴圈

Spring Boot 專案的驗證迴圈:建構、靜態分析、含覆蓋率的測試、安全掃描以及發佈或 PR 前的差異審查。

Spring Boot 驗證迴圈 是什麼?

這個技能定義了一個完整的驗證迴圈,專為 Spring Boot 專案設計,可作為 AI 編碼助手(如 Claude Code 或 Cursor)的指引。它涵蓋了從建構、靜態分析、測試(單元、整合、API)與覆蓋率、安全掃描到差異審查的所有必要步驟,確保程式碼在合併或部署前達到高品質標準。使用者可以透過明確的階段劃分和指令,自動化執行檢查,並根據輸出模板快速評估專案是否就緒。該技能支援 Maven 和 Gradle 兩種建構工具,並整合了常見的 Java 測試與安全工具(如 JUnit 5、Testcontainers、MockMvc、OWASP Dependency Check、SpotBugs、PMD、Checkstyle 等),幫助開發團隊維持一致的程式碼品質與安全性。

相容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/springboot-verification

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開啟一個已預先載入此 Agent Skill 的新對話。

說明文件

Spring Boot 驗證迴圈 是做什麼的?

在 PR 之前、重大變更之後以及部署之前執行。

何時啟用

  • 在為 Spring Boot 服務開啟 Pull Request 之前
  • 在重大重構或相依套件升級之後
  • 預備部署至暫存或正式環境的驗證
  • 執行完整的建構 → 語法檢查 → 測試 → 安全掃描流程
  • 驗證測試涵蓋率符合門檻

第一階段:建構

mvn -T 4 clean verify -DskipTests
# 或
./gradlew clean assemble -x test

如果建構失敗,請停止並修正。

第二階段:靜態分析

Maven(常見外掛):

mvn -T 4 spotbugs:check pmd:check checkstyle:check

Gradle(如有設定):

./gradlew checkstyleMain pmdMain spotbugsMain

第三階段:測試 + 涵蓋率

mvn -T 4 test
mvn jacoco:report   # 驗證 80% 以上涵蓋率
# 或
./gradlew test jacocoTestReport

報告:

  • 總測試數、通過/失敗
  • 涵蓋率 %(程式行/分支)

單元測試

以模擬的相依隔離測試服務邏輯:

@ExtendWith(MockitoExtension.class)
class UserServiceTest {

  @Mock private UserRepository userRepository;
  @InjectMocks private UserService userService;

  @Test
  void createUser_validInput_returnsUser() {
    var dto = new CreateUserDto("Alice", "[email protected]");
    var expected = new User(1L, "Alice", "[email protected]");
    when(userRepository.save(any(User.class))).thenReturn(expected);

    var result = userService.create(dto);

    assertThat(result.name()).isEqualTo("Alice");
    verify(userRepository).save(any(User.class));
  }

  @Test
  void createUser_duplicateEmail_throwsException() {
    var dto = new CreateUserDto("Alice", "[email protected]");
    when(userRepository.existsByEmail(dto.email())).thenReturn(true);

    assertThatThrownBy(() -> userService.create(dto))
        .isInstanceOf(DuplicateEmailException.class);
  }
}

使用 Testcontainers 的整合測試

針對真實資料庫進行測試,而非 H2:

@SpringBootTest
@Testcontainers
class UserRepositoryIntegrationTest {

  @Container
  static PostgreSQLContainer<?> postgres = new PostgreSQLContainer<>("postgres:16-alpine")
      .withDatabaseName("testdb");

  @DynamicPropertySource
  static void configureProperties(DynamicPropertyRegistry registry) {
    registry.add("spring.datasource.url", postgres::getJdbcUrl);
    registry.add("spring.datasource.username", postgres::getUsername);
    registry.add("spring.datasource.password", postgres::getPassword);
  }

  @Autowired private UserRepository userRepository;

  @Test
  void findByEmail_existingUser_returnsUser() {
    userRepository.save(new User("Alice", "[email protected]"));

    var found = userRepository.findByEmail("[email protected]");

    assertThat(found).isPresent();
    assertThat(found.get().getName()).isEqualTo("Alice");
  }
}

使用 MockMvc 進行 API 測試

在完整的 Spring 環境中測試 Controller 層:

@WebMvcTest(UserController.class)
class UserControllerTest {

  @Autowired private MockMvc mockMvc;
  @MockBean private UserService userService;

  @Test
  void createUser_validInput_returns201() throws Exception {
    var user = new UserDto(1L, "Alice", "[email protected]");
    when(userService.create(any())).thenReturn(user);

    mockMvc.perform(post("/api/users")
            .contentType(MediaType.APPLICATION_JSON)
            .content("""
                {"name": "Alice", "email": "[email protected]"}
                "))
        .andExpect(status().isCreated())
        .andExpect(jsonPath("$.name").value("Alice"));
  }

  @Test
  void createUser_invalidEmail_returns400() throws Exception {
    mockMvc.perform(post("/api/users")
            .contentType(MediaType.APPLICATION_JSON)
            .content("""
                {"name": "Alice", "email": "not-an-email"}
                "))
        .andExpect(status().isBadRequest());
  }
}

第四階段:安全掃描

# 相依套件 CVE
mvn org.owasp:dependency-check-maven:check
# 或
./gradlew dependencyCheckAnalyze

# 原始碼中的機密資訊
grep -rn "password\s*=\s*\"" src/ --include="*.java" --include="*.yml" --include="*.properties"
grep -rn "sk-\|api_key\|secret" src/ --include="*.java" --include="*.yml"

# 機密資訊(Git 歷史)
git secrets --scan  # 如有設定

常見安全發現

# 檢查 System.out.println(請改用日誌)
grep -rn "System\.out\.print" src/main/ --include="*.java"

# 檢查回應中直接顯示原始例外訊息
grep -rn "e\.getMessage()" src/main/ --include="*.java"

# 檢查萬用字元 CORS
grep -rn "allowedOrigins.*\*" src/main/ --include="*.java"

第五階段:語法格式化(可選閘道)

mvn spotless:apply   # 如果有使用 Spotless 外掛
./gradlew spotlessApply

第六階段:差異審查

git diff --stat
git diff

檢查清單:

  • 無遺留除錯日誌(System.out、未包裝的 log.debug)
  • 有意義的錯誤訊息和 HTTP 狀態碼
  • 必要的交易管理和驗證
  • 設定變更已記錄

輸出模板

驗證報告
===================
建構:     [通過/失敗]
靜態分析:  [通過/失敗] (spotbugs/pmd/checkstyle)
測試:     [通過/失敗] (X/Y 通過,Z% 涵蓋率)
安全:     [通過/失敗] (CVE 發現數:N)
差異:     [變更檔案數]

整體:     [就緒 / 未就緒]

待解決問題:
1. ...
2. ...

持續模式

  • 遇到重大變更時,或長時間作業階段中每 30–60 分鐘重新執行各階段
  • 保持簡短迴圈:mvn -T 4 test + spotbugs 以獲得快速反饋

記住:快速反饋勝過事後驚喜。嚴格把關——在正式系統中將警告視為缺陷。

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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