Copenhagen Denmark Failure is not an Option Error handling strategies for Kotlin programs Nat Pryce & Duncan McGregor @natpryce, @duncanmcg

What is failure?

Programs can go wrong for so many reasons! ● Invalid Input ○ Strings with invalid values ○ Numbers out of range ○ Unexpectedly null pointers ● External Failure ○ File not found ○ Socket timeout ● Programming Errors ○ Array out of bounds ○ Invalid state ○ Integer overflow ● System Errors ○ Out of memory ● …

Error handling is hard to get right "Without correct error propagation, any comprehensive failure policy is useless … We find that error handling is occasionally correct. Specifically, we see that low-level errors are sometimes lost as they travel through [...] many layers [...]" EIO: Error handling is occasionally correct. H. S. Gunawi, et al. In Proc. of the 6th USENIX Conference on File and Storage Technologies, FAST’08, 2008. "Almost all catastrophic failures (92%) are the result of incorrect handling of non-fatal errors explicitly signaled in software" Simple Testing Can Prevent Most Critical Failures: An Analysis of Production Failures in Distributed Data-Intensive Systems. Ding Yuan, et al., University of Toronto. In Proceedings of the 11th USENIX Symposium on Operating Systems Design and Implementation, OSDI14, 2014

Java tried to help with checked exceptions Checked Exception Something failed in the program's environment. The program could recover. The type checker ensures that the programmer considers all possible environmental failures in their design. RuntimeException A programmer made a mistake that was detected by the runtime. All bets are off (because of non-transactional mutable state) Error The JVM can no longer guarantee the semantics of the language. All bets are off.

But history happened...

And now...

What is the best way to handle errors in Kotlin?

It depends

What it depends on will change

We could… just use exceptions

It's easy to throw exceptions – maybe too easy fun handlePost(request: HttpRequest): HttpResponse { val action = try { parseRequest_1(request) } catch (e: NumberFormatException) { return HttpResponse(HTTP_BAD_REQUEST) } catch (e: NoSuchElementException) { return HttpResponse(HTTP_BAD_REQUEST) } perform(action) return HttpResponse(HTTP_OK) } fun parseRequest(request: HttpRequest): BigInteger { val form = request.readForm() return form["id"]?.toBigInteger() ?: throw NoSuchElementException("id missing") }

Categorise errors as they cross domain boundaries fun handlePost(request: HttpRequest): HttpResponse { val action = try { parseRequest(request) } catch (e: BadRequest) { return HttpResponse(HTTP_BAD_REQUEST) } perform(action) return HttpResponse(HTTP_OK) } fun parseRequest(request: HttpRequest) = try { val form = request.readForm() form["id"]?.toBigInteger() ?: throw BadRequest("id missing") } catch(e: NumberFormatException) { throw BadRequest(e) }

But code using exceptions can be difficult to change. fun handlePost(request: HttpRequest): HttpResponse { val action = try { parseRequest(request) } catch (e: BadRequest) { return HttpResponse(HTTP_BAD_REQUEST) } perform(action) return HttpResponse(HTTP_OK) } fun parseRequest(request: HttpRequest) = try { val json = request.readJson() json["id"].textValue().toBigInteger() } catch(e: NumberFormatException) { throw BadRequest(e) } Can you spot the bug?

Exception handling bugs may not be visible & are not typechecked fun handlePost(request: HttpRequest): HttpResponse { val action = try { parseRequest(request) } catch (e: BadRequest) { return HttpResponse(HTTP_BAD_REQUEST) } perform(action) return HttpResponse(HTTP_OK) } fun parseRequest(request: HttpRequest) = try { val json = request.readJson() json["id"].textValue().toBigInteger() } catch(e: NumberFormatException) { throw BadRequest(e) } Can throw JsonException ... which is not handled here ... … and so propagates to the HTTP layer, which returns 500 instead of 400

Fuzz test to ensure no unexpected exceptions @Test fun `Does not throw unexpected exceptions on parse failure`() { Random().mutants(1000, validInput) .forEach { possiblyInvalidInput -> try { parse(possiblyInvalidInput) } catch (e: BadRequest) { /* allowed */ } catch (e: Exception) { fail("unexpected exception $e for: $possiblyInvalidInput") } } } https://github.com/npryce/snodge

Exceptions are fine when... … the behaviour of the program does not depend on the type of error. For example ● It can just crash (and maybe rely on a supervisor to restart it) ● It can write a message to stderr and return an error code to the shell ● It can display a dialog and let the user correct the problem Be aware of when that context changes

Avoid errors

Total Functions fun readFrom(uri: String): ByteArray? { ... } fun readFrom(uri: URI): ByteArray? { ... } class Fetcher(private val config: Config) { fun fetch(path: String): ByteArray? { val uri: URI = config[BASE_URI].resolve(path) return readFrom(uri) } } class Fetcher(private val base: URI) { constructor(config: Config) : this(config[BASE_URI]) fun fetch(path: String): ByteArray? = readFrom(base.resolve(path)) }

We could… use null to represent errors

A common convention in the standard library /** * Parses the string as an [Int] number and returns the result * or `null` if the string is not a valid representation of a number. */ @SinceKotlin("1.1") public fun String.toIntOrNull(): Int? = ...

Errors can be handled with the elvis operator fun handleGet(request: HttpRequest): HttpResponse { val count = request["count"].firstOrNull() ?.toIntOrNull() ?: return HttpResponse(HTTP_BAD_REQUEST).body("invalid count") val startTime = request["from"].firstOrNull() ?.let { ISO_INSTANT.parseInstant(it) } ?: return HttpResponse(HTTP_BAD_REQUEST).body("invalid from time") ...

But the same construct represents absence and error fun handleGet(request: HttpRequest): HttpResponse { val count = request["count"].firstOrNull()?.let { it.toIntOrNull() ?: return HttpResponse(HTTP_BAD_REQUEST) .body("invalid count parameter") } ?: 100 val startTime = request["from"].firstOrNull()?.let { ISO_INSTANT.parseInstant(it) ?: return HttpResponse(HTTP_BAD_REQUEST) .body("invalid from parameter") } ?: Instant.now() ...

Convert exceptions to null close to their source fun DateTimeFormatter.parseInstant(s: String): Instant? = try { parse(s, Instant::from) } catch (e: DateTimeParseException) { null }

Using null for error cases is fine when... … the cause of an error is obvious from the context. … optionality and errors are not handled by the same code. For example ● Parsing a simple typed value from a string ● Looking up data that may not be present Be aware of when that context changes And fuzz test to ensure no unexpected exceptions.

Move errors to the outer layers

Move errors to the outer layers fun process(src: URI, dest: File) { val things = readFrom(src) process(things, dest) } fun process(things: List, dest: File) { ... } fun process(src: URI, dest: File) { val things = readFrom(src) dest.writeLines(process(things)) } fun process(things: List): List { ... }

We could… use an algebraic data type (in Kotlin, a sealed class hierarchy) "Don't mention monad. I mentioned it once but I think I got away with it all right."

An example Result type sealed class Result data class Success(val value: T) : Result() data class Failure(val reason: E) : Result() This example is from Result4k Other Result types are available from your preferred supplier* * Maven Central

You are forced to consider the failure case val result = operationThatCanFail() when (result) { is Success -> doSomethingWith(result.value) is Failure -> handleError(result.reason) } Cannot get the value from a Result without ensuring that it is a Success ☛ Flow-sensitive typing means no casting But awkward to use for every function call that might fail And... how should we represent the failure reasons?

Convenience operations instead of when expressions fun handlePost(request: HttpRequest): HttpResponse = request.readJson() .flatMap { json -> json.toCommand() } .flatMap(::performCommand) .map { outcome -> outcome.toHttpResponse() } .mapFailure { errorCode -> errorCode.toHttpResponse() } .get()

No language support for monads fun handlePost(request: HttpRequest): Result = request.readJson() .flatMap { json -> json.toCommand() .flatMap { command -> loadResourceFor(request) .flatMap { resource -> performCommand(resource, command) .map { outcome -> outcome.toHttpResponseFor(request) } } } } http://wiki.c2.com/?ArrowAntiPattern

Arrow's binding API Very clever emulation of Haskell's do syntax for monadic binding fun handlePost(request: HttpRequest): Either = Either.fx { val (json) = request.readJson() val (command) = json.toCommand() val (resource) = loadResource(request) val (outcome) = performCommand(resource, command) outcome.toHttpResponseFor(request) }

fun handlePost(request: HttpRequest): Result { val json = request.readJson().onFailure { return it } val command = json.toCommand().onFailure { return it } val resource = loadResource(request).onFailure { return it } val outcome = performCommand(resource, command).onFailure { return it } return Success(outcome.toHttpResponseFor(request)) } Flatten nesting with inline functions & early returns inline fun Result.onFailure(block: (Failure) -> Nothing): T = when (this) { is Success -> value is Failure -> block(this) }

Exceptions or sealed class hierarchy? One hierarchy for all errors? ● You lose the exhaustiveness check in when expressions ● Less assistance from the type checker: bugs creep into error handling code Separate hierarchies for bounded contexts? ● Type checker keeps you honest ● But more work: must be translated or wrapped as they cross boundaries Do we care about stack traces? (Nat’s conclusion: only for programming errors) How to model error reasons in the Failure case?

A Result type is fine when... … your team are used to a functional programming style … you don't need stack traces For example ● Propagating exceptional cases in business logic to web pages ● Looking up data that may not be present Be aware of when that context changes And convert exceptions to Failures close to source & fuzz test

Design your system to be robust to errors

The sweet spot for our system ● Null for "simple" parse errors ● Result to reporting the location of parse errors in "complicated" data ● Result for explicit errors from application logic ● Result when errors are recoverable ● Exceptions for environmental failures and programmer error ● All exceptions handled in one place ● Fuzz test to make sure we do not propagate unexpected exceptions ● Push code that can fail to the outer layers ● Prefer immutable data ● Carefully control mutable data so exceptions don’t break persistent state

What's the sweet spot for your system?

#KotlinConf THANK YOU AND REMEMBER TO VOTE Nat Pryce @natpryce Duncan McGregor @duncanmcg Failure is not an Option http://oneeyedmen.com/failure-is-not-an-option-part-1.html Result4K https://github.com/npryce/result4k Snodge https://github.com/npryce/snodge

Failure is not an Option Error handling strategies for Kotlin programs Nat Pryce & Duncan McGregor

Early Error Handling Strategies

Early Exceptions

Compose error-prone and error-free code

So far

The sweet spot that works for us