| name | kotlin-sum-types |
| description | Parse, don't validate - using sealed classes for type-safe validation and state representation. Model valid/invalid states explicitly, validate at boundaries, operate on valid types internally. Use when implementing validation with sealed classes, modeling valid/invalid states, or applying parse-don't-validate patterns in Kotlin. The pattern is transferrable to other languages, though the mechanism will differ. |
| domain | kotlin |
| tags | ["kotlin","sealed-class","validation","parse-dont-validate"] |
STARTER_CHARACTER = 🔀
Parse, Don't Validate with Kotlin Sealed Classes
Represent validation states explicitly using sealed classes. This makes invalid states unrepresentable in your domain logic and pushes validation to system boundaries.
Core Principle
Parse, don't validate means transforming untyped input into strongly-typed domain objects at the boundary, carrying proof of validity through the type system.
Instead of:
fun processEmail(email: String) {
if (!isValid(email)) throw ValidationException()
}
Do this:
fun processEmail(email: ValidEmail) {
}
Basic Pattern: Valid/Invalid States
Use sealed classes to represent parsed data that can be either valid or invalid:
sealed class Email {
data class ValidEmail(
val user: String,
val domain: String,
) : Email() {
fun stringRepresentation(): String = "$user@$domain"
}
data class InvalidEmail(
val value: String,
val _errors: List<ValidationError>,
) : Email(), InvalidDataClass {
override fun getErrors(): List<ValidationError> = _errors
}
companion object {
@JvmStatic
@JsonCreator
fun create(createValue: String): Email =
if (createValue.contains("@")) {
createValue.split("@").let { ValidEmail(it.first(), it.last()) }
} else {
InvalidEmail(
createValue,
listOf(ValidationError("", "Not a valid Email", createValue))
)
}
}
}
Key elements:
- Sealed class as parent (Email)
- ValidEmail with parsed structure (user, domain)
- InvalidEmail preserving original value + errors
- Static
create() factory for parsing
@JsonCreator for Jackson integration
Validation Error Model
Standard error representation:
data class ValidationError(
val path: String,
val message: String,
val value: String,
)
interface InvalidDataClass {
fun hasErrors(): Boolean = getErrors().isNotEmpty()
fun getErrors(): List<ValidationError>
}
All invalid states implement InvalidDataClass to expose errors uniformly.
Composite Validation
Build complex types by composing validated types:
sealed class Address {
data class ValidAddress(
val streetName: String,
val city: String,
val postCode: String,
val country: String,
) : Address()
data class InvalidAddress(
val streetName: String?,
val city: String?,
val postCode: String?,
val country: String?,
val _errors: List<ValidationError>,
) : Address(), InvalidDataClass {
override fun getErrors(): List<ValidationError> = _errors
}
companion object {
@JvmStatic
@JsonCreator
fun create(
streetName: String?,
city: String?,
postCode: String?,
country: String?,
): Address {
if (streetName.isNullOrEmpty() || city.isNullOrEmpty() ||
postCode.isNullOrBlank() || country.isNullOrBlank()) {
return InvalidAddress(
streetName, city, postCode, country,
listOf(ValidationError("", "Missing required fields", "..."))
)
}
return ValidAddress(streetName, city, postCode, country)
}
}
}
InvalidAddress preserves all input: Even invalid data is kept so you can return meaningful error messages to users.
Nested Valid States
Valid states can have their own hierarchy:
sealed class RegistrationForm {
data class Invalid(
val email: Email,
val anonymous: Boolean,
val name: String?,
val address: Address?,
val _errors: List<ValidationError>,
) : RegistrationForm(), InvalidDataClass {
override fun getErrors(): List<ValidationError> = _errors
}
sealed class Valid(
open val email: Email.ValidEmail,
) : RegistrationForm() {
data class AnonymousRegistration(
val _email: Email.ValidEmail,
) : Valid(_email)
data class Registration(
val _email: Email.ValidEmail,
val name: String,
val address: Address.ValidAddress,
) : Valid(_email)
}
companion object {
@JvmStatic
@JsonCreator
fun create(
email: Email,
anonymous: Boolean,
name: String?,
address: Address?,
): RegistrationForm {
val errors = mapOf("email" to email, "address" to address)
.filter { it.value is InvalidDataClass }
.flatMap { (key, value) ->
(value as InvalidDataClass).getErrors()
.map { error ->
error.copy(
path = key + if (error.path.isNotEmpty()) ".${error.path}" else ""
)
}
}
return when {
errors.isNotEmpty() -> Invalid(email, anonymous, name, address, errors)
anonymous -> Valid.AnonymousRegistration(email as Email.ValidEmail)
name != null -> Valid.Registration(
email as Email.ValidEmail,
name,
address as Address.ValidAddress
)
else -> Invalid(
email, anonymous, name, address,
listOf(ValidationError("", "Invalid combination", ""))
)
}
}
}
}
Note the types:
Valid.Registration requires Email.ValidEmail and Address.ValidAddress
- Invalid case can contain any
Email and Address (valid or invalid)
- Errors are propagated with paths ("email", "address.city")
Controller Pattern
Handle valid/invalid cases at the boundary using when:
sealed class ControllerResponse {
data class OkResponse(val result: String) : ControllerResponse()
data class ErrorResponse(val errors: List<ValidationError>) : ControllerResponse()
}
class RegistrationController(
private val registrationService: RegistrationService,
) {
private val mapper = jacksonObjectMapper()
fun registerUser(jsonString: String): ControllerResponse =
when (val parsed: RegistrationForm = mapper.readValue(jsonString)) {
is RegistrationForm.Valid -> {
registrationService.createNewRegistration(parsed)
when (parsed) {
is RegistrationForm.Valid.Registration ->
ControllerResponse.OkResponse("Congrats ${parsed.name}!")
is RegistrationForm.Valid.AnonymousRegistration ->
ControllerResponse.OkResponse("Congrats!")
}
}
is RegistrationForm.Invalid ->
ControllerResponse.ErrorResponse(parsed.getErrors())
}
}
Key aspects:
- Parse JSON at the boundary
when expression handles valid/invalid exhaustively
- Service receives only valid types
- Errors automatically collected and returned
Jackson Integration
Use @JsonCreator to hook into Jackson parsing:
companion object {
@JvmStatic
@JsonCreator
fun create(param1: Type1, param2: Type2): SealedClass {
}
}
Jackson calls create() during deserialization, giving you control over validation.
Dependencies:
implementation("com.fasterxml.jackson.module:jackson-module-kotlin")
Usage:
val mapper = jacksonObjectMapper()
val parsed: RegistrationForm = mapper.readValue(jsonString)
Benefits
Type Safety:
- Invalid states are unrepresentable in domain logic
- Compiler prevents passing invalid data to functions expecting valid types
when expressions ensure all cases are handled
Error Collection:
- Multiple validation errors collected in one pass
- Nested errors preserve field paths
- Original invalid values preserved for debugging
Maintainability:
- Validation logic centralized in
create() factories
- Domain logic operates only on valid types
- Clear boundary between validated and unvalidated data
Refactoring Safety:
- Adding new fields to valid types is a compiler error if not handled
- Changing validation rules doesn't affect domain logic
- IDE autocomplete shows all valid/invalid states
When to Use This Pattern
Use sealed classes for validation when:
- Parsing external input (JSON, CSV, user forms)
- Multiple fields must be validated together
- You need to collect multiple validation errors
- Invalid data should be preserved for error reporting
- Validation rules are complex or change frequently
Don't use when:
- Simple non-null checks (use Kotlin's
? types)
- Single-field validation with no composition
- Data is already validated by external system (database constraints)
- Performance is critical (adds allocation overhead)
Testing Strategy
Test valid state creation:
@Test
fun shouldParseValidEmail() {
val parsed = Email.create("user@example.com")
assertThat(parsed).isInstanceOf(Email.ValidEmail::class.java)
(parsed as Email.ValidEmail).let {
assertThat(it.user).isEqualTo("user")
assertThat(it.domain).isEqualTo("example.com")
}
}
Test invalid state creation:
@Test
fun shouldParseInvalidEmail() {
val parsed = Email.create("not-an-email")
assertThat(parsed).isInstanceOf(Email.InvalidEmail::class.java)
(parsed as Email.InvalidEmail).let {
assertThat(it.value).isEqualTo("not-an-email")
assertThat(it.getErrors()).isNotEmpty()
}
}
Test composite validation:
@Test
fun shouldCollectNestedErrors() {
val form = RegistrationForm.create(
email = Email.create("invalid"),
anonymous = false,
name = null,
address = Address.create(null, null, null, null)
)
assertThat(form).isInstanceOf(RegistrationForm.Invalid::class.java)
(form as RegistrationForm.Invalid).let {
val errorPaths = it.getErrors().map { e -> e.path }
assertThat(errorPaths).contains("email", "address")
}
}
Test controller handling:
@Test
fun shouldReturnErrorResponseForInvalidInput() {
val response = controller.registerUser("""{"email": "bad"}""")
assertThat(response).isInstanceOf(ControllerResponse.ErrorResponse::class.java)
(response as ControllerResponse.ErrorResponse).let {
assertThat(it.errors).isNotEmpty()
}
}
Real-World Example
See complete working example:
Anti-Patterns
Don't validate in the domain:
fun processRegistration(email: String, name: String) {
require(email.contains("@")) { "Invalid email" }
require(name.isNotBlank()) { "Name required" }
}
Do validation at boundaries, pass validated types to domain:
fun processRegistration(registration: RegistrationForm.Valid.Registration) {
}
Don't lose original invalid values:
data class InvalidEmail(val _errors: List<ValidationError>) : Email()
Keep the original value:
data class InvalidEmail(
val value: String,
val _errors: List<ValidationError>
) : Email()
Don't use exceptions for expected validation:
fun create(email: String): ValidEmail {
if (!isValid(email)) throw ValidationException()
return ValidEmail(...)
}
Return sealed class representing valid/invalid:
fun create(email: String): Email {
if (!isValid(email)) return InvalidEmail(...)
return ValidEmail(...)
}
Related Patterns
- Railway-Oriented Programming: Result<T, E> types (similar but more functional)
- Type-Driven Development: Using types to guide design
- Domain-Driven Design: Validation at aggregate boundaries
References