Failure is not an Option. Error handling strategies for Kotlin programs

By Nat Pryce and Duncan McGregor.

Kotlin largely inherits Java's exception mechanism, but exceptions and functional programming are uneasy bedfellows, leading to most projects adopting a wing-and-a-prayer as their error handling strategy.

It needn’t be so ad-hoc though. We compare and contrast different techniques for handling errors in Kotlin programs. We will discuss the sweet spots, pitfalls and trade-offs encountered in each technique, illustrated with examples from real projects.

Presented at KotlinConf 2019.

Video: https://youtu.be/pvYAQNT4o0I

Transcript

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

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2. What is failure?
   

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3. 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
   ● …
   

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4. 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
   

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5. 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.
   

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6. But history happened...
   

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7. And now...
   

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8. What is the best way to
   handle errors in Kotlin?
   

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9. It depends
   

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10. What it depends on will change
    

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11. We could…
    just use exceptions
    

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12. 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")
    }
    

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13. 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)
    }
    

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14. 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?
    

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15. 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
    

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16. 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
    

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17. 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
    

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18. Avoid errors
    
    

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19. 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))
    }
    

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20. We could…
    use null to represent errors
    

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21. 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? = ...
    

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22. 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")
    ...
    

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23. 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()
    ...
    

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

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25. 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.
    

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26. Move errors to the outer layers
    
    

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27. 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 {
    ...
    }
    

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28. 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."
    

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29. 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
    

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30. 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?
    

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31. 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()
    

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32. 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
    

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33. 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)
    }
    

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34. 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)
    }
    

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35. 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?
    

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36. 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
    

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37. Design your system to be
    robust to errors
    
    

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38. 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
    

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39. What's the sweet spot for your system?
    

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40. #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
    

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

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42. Early Error Handling Strategies
    

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43. Early Exceptions
    

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44. Compose error-prone and error-free code
    

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45. So far
    

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46. The sweet spot that works for us
    

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