본문으로 건너뛰기
cccskills
무료GitHub에 공개

java-refactoring-extract-method

Refactor Java methods by extracting related blocks into separate, clearly named methods. Assess method length and complexity, preserve existing functionality, and return complete Java 17 methods with brief comments explaining each newly extracted method.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Refactoring using Extract Methods in Java Language

설치 방법 보기

이럴 때 유용합니다

  • Split a long Java method into smaller methods
  • Separate distinct operations within complex methods
  • Name extracted logic to clarify its purpose
  • Prepare existing Java code for testing and maintenance

포함된 파일(1)

  • SKILL.md3.4 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Refactoring Java Methods with Extract Method

Role

You are an expert in refactoring Java methods.

Below are 2 examples (with titles code before and code after refactoring) that represents Extract Method.

Code Before Refactoring 1:

public FactLineBuilder setC_BPartner_ID_IfValid(final int bpartnerId) {
	assertNotBuild();
	if (bpartnerId > 0) {
		setC_BPartner_ID(bpartnerId);
	}
	return this;
}

Code After Refactoring 1:

public FactLineBuilder bpartnerIdIfNotNull(final BPartnerId bpartnerId) {
	if (bpartnerId != null) {
		return bpartnerId(bpartnerId);
	} else {
		return this;
	}
}
public FactLineBuilder setC_BPartner_ID_IfValid(final int bpartnerRepoId) {
	return bpartnerIdIfNotNull(BPartnerId.ofRepoIdOrNull(bpartnerRepoId));
}

Code Before Refactoring 2:

public DefaultExpander add(RelationshipType type, Direction direction) {
     Direction existingDirection = directions.get(type.name());
     final RelationshipType[] newTypes;
     if (existingDirection != null) {
          if (existingDirection == direction) {
               return this;
          }
          newTypes = types;
     } else {
          newTypes = new RelationshipType[types.length + 1];
          System.arraycopy(types, 0, newTypes, 0, types.length);
          newTypes[types.length] = type;
     }
     Map<String, Direction> newDirections = new HashMap<String, Direction>(directions);
     newDirections.put(type.name(), direction);
     return new DefaultExpander(newTypes, newDirections);
}

Code After Refactoring 2:

public DefaultExpander add(RelationshipType type, Direction direction) {
     Direction existingDirection = directions.get(type.name());
     final RelationshipType[] newTypes;
     if (existingDirection != null) {
          if (existingDirection == direction) {
               return this;
          }
          newTypes = types;
     } else {
          newTypes = new RelationshipType[types.length + 1];
          System.arraycopy(types, 0, newTypes, 0, types.length);
          newTypes[types.length] = type;
     }
     Map<String, Direction> newDirections = new HashMap<String, Direction>(directions);
     newDirections.put(type.name(), direction);
     return (DefaultExpander) newExpander(newTypes, newDirections);
}
protected RelationshipExpander newExpander(RelationshipType[] types,
          Map<String, Direction> directions) {
     return new DefaultExpander(types, directions);
}

Task

Apply Extract Method to improve readability, testability, maintainability, reusability, modularity, cohesion, low coupling, and consistency.

Always return a complete and compilable method (Java 17).

Perform intermediate steps internally:

  • First, analyze each method and identify those exceeding thresholds:
    • LOC (Lines of Code) > 15
    • NOM (Number of Statements) > 10
    • CC (Cyclomatic Complexity) > 10
  • For each qualifying method, identify code blocks that can be extracted into separate methods.
  • Extract at least one new method with a descriptive name.
  • Output only the refactored code inside a single java block.
  • Do not remove any functionality from the original method.
  • Include a one-line comment above each new method describing its purpose.

Code to be Refactored:

Now, assess all methods with high complexity and refactor them using Extract Method

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Map an existing codebase into seven documents covering its technology, structure, architecture, conventions, integrations, tests, and concerns. Link findings to file evidence, mark unknowns, and highlight differences between stated plans and the actual implementation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Get oriented in an unfamiliar codebase
  • Prepare documentation for a project handover
  • Compare documented architecture with implementation
github/awesome-copilot4만2026년 10월 17일 업데이트

Assess a repository’s readiness for AI agents with AgentRC and generate a standalone HTML dashboard. Review scores across nine areas, see prioritized improvements, and optionally apply scoring policies tailored to an organization.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Assessing a repository’s readiness for AI agents
  • Prioritizing improvements from assessment results
  • Reviewing scores under an organization’s own policy
github/awesome-copilot4만2026년 10월 17일 업데이트

Generate coding agent instruction files from a project's actual code using AgentRC. Capture detected languages, frameworks, and conventions in one shared file or split rules by topic and project area, with a preview before writing.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Create project instructions for VS Code Copilot
  • Refresh agent rules after project changes
  • Split monorepo instructions by project area
github/awesome-copilot4만2026년 10월 17일 업데이트

Customize AgentRC readiness assessments to match team or organization standards. Choose or create policies that adjust check importance, disable irrelevant checks, set pass thresholds, and define requirements for automated checks in CI workflows.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Set shared readiness standards across an organization
  • Focus assessments on AI tooling
  • Adjust the importance of individual checks
github/awesome-copilot4만2026년 10월 17일 업데이트

Analyze supplied ad performance data to identify wasted spend, strong campaigns, and next tests. Compare channels, assess whether test differences are meaningful, and produce budget reallocation recommendations with a prioritized action plan.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Identify ads and keywords to pause
  • Find campaigns and audiences worth scaling
  • Assess whether A/B test results are meaningful
github/awesome-copilot4만2026년 10월 17일 업데이트

Turn code files into learning resources by adding comments that explain syntax, programming concepts, and design choices. Adjust explanation depth and repetition to the reader’s knowledge while preserving file structure, encoding, and syntax.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Add beginner-friendly explanations to existing code
  • Document the reasoning behind syntax and design choices
  • Adjust comment depth for readers with different experience
github/awesome-copilot4만2026년 10월 17일 업데이트

github의 스킬 모두 보기

이 스킬의 문제 신고