java-coding-standards
Adheres to Java coding standards for Spring Boot services, covering naming conventions, immutability, etc., to ensure code quality and maintainability.
npx skills add https://github.com/affaan-m/everything-claude-code --skill java-coding-standardsBefore / After Comparison
1 组The team's Java code style was inconsistent, and naming was chaotic, leading to poor code readability and difficult maintenance. New members struggled to get up to speed, code review efficiency was low, increasing project risks and development costs.
By adhering to Spring Boot service Java coding standards, unifying naming, immutability, and Optional usage, code quality has significantly improved. It is now easier to understand and maintain, accelerating team collaboration and project delivery.
Java Coding Standards
Standards for readable, maintainable Java (17+) code in Spring Boot services.
When to Activate
- Writing or reviewing Java code in Spring Boot projects
- Enforcing naming, immutability, or exception handling conventions
- Working with records, sealed classes, or pattern matching (Java 17+)
- Reviewing use of Optional, streams, or generics
- Structuring packages and project layout
Core Principles
- Prefer clarity over cleverness
- Immutable by default; minimize shared mutable state
- Fail fast with meaningful exceptions
- Consistent naming and package structure
Naming
// ✅ Classes/Records: PascalCase
public class MarketService {}
public record Money(BigDecimal amount, Currency currency) {}
// ✅ Methods/fields: camelCase
private final MarketRepository marketRepository;
public Market findBySlug(String slug) {}
// ✅ Constants: UPPER_SNAKE_CASE
private static final int MAX_PAGE_SIZE = 100;
Immutability
// ✅ Favor records and final fields
public record MarketDto(Long id, String name, MarketStatus status) {}
public class Market {
private final Long id;
private final String name;
// getters only, no setters
}
Optional Usage
// ✅ Return Optional from find* methods
Optional<Market> market = marketRepository.findBySlug(slug);
// ✅ Map/flatMap instead of get()
return market
.map(MarketResponse::from)
.orElseThrow(() -> new EntityNotFoundException("Market not found"));
Streams Best Practices
// ✅ Use streams for transformations, keep pipelines short
List<String> names = markets.stream()
.map(Market::name)
.filter(Objects::nonNull)
.toList();
// ❌ Avoid complex nested streams; prefer loops for clarity
Exceptions
- Use unchecked exceptions for domain errors; wrap technical exceptions with context
- Create domain-specific exceptions (e.g.,
MarketNotFoundException) - Avoid broad
catch (Exception ex)unless rethrowing/logging centrally
throw new MarketNotFoundException(slug);
Generics and Type Safety
- Avoid raw types; declare generic parameters
- Prefer bounded generics for reusable utilities
public <T extends Identifiable> Map<Long, T> indexById(Collection<T> items) { ... }
Project Structure (Maven/Gradle)
src/main/java/com/example/app/
config/
controller/
service/
repository/
domain/
dto/
util/
src/main/resources/
application.yml
src/test/java/... (mirrors main)
Formatting and Style
- Use 2 or 4 spaces consistently (project standard)
- One public top-level type per file
- Keep methods short and focused; extract helpers
- Order members: constants, fields, constructors, public methods, protected, private
Code Smells to Avoid
- Long parameter lists → use DTO/builders
- Deep nesting → early returns
- Magic numbers → named constants
- Static mutable state → prefer dependency injection
- Silent catch blocks → log and act or rethrow
Logging
private static final Logger log = LoggerFactory.getLogger(MarketService.class);
log.info("fetch_market slug={}", slug);
log.error("failed_fetch_market slug={}", slug, ex);
Null Handling
- Accept
@Nullableonly when unavoidable; otherwise use@NonNull - Use Bean Validation (
@NotNull,@NotBlank) on inputs
Testing Expectations
- JUnit 5 + AssertJ for fluent assertions
- Mockito for mocking; avoid partial mocks where possible
- Favor deterministic tests; no hidden sleeps
Remember: Keep code intentional, typed, and observable. Optimize for maintainability over micro-optimizations unless proven necessary.
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