Erlang ↔ Haskell Conversion

Bidirectional conversion between Erlang and Haskell. This skill extends meta-convert-dev with Erlang↔Haskell specific type mappings, idiom translations, and concurrency patterns for translating between these functional languages with fundamentally different type systems and runtime models.

This Skill Extends

• meta-convert-dev - Foundational conversion patterns (APTV workflow, testing strategies)

For general concepts like the Analyze → Plan → Transform → Validate workflow, testing strategies, and common pitfalls, see the meta-skill first.

This Skill Adds

• Type mappings: Erlang dynamic types → Haskell static types
• Idiom translations: Erlang patterns → idiomatic Haskell
• Concurrency models: OTP behaviors → STM/async patterns
• Error handling: let-it-crash → Maybe/Either types
• Message passing: Process mailboxes → Channels/TQueue
• Supervision: Supervisor trees → immortal/distributed-process

This Skill Does NOT Cover

• General conversion methodology - see meta-convert-dev
• Erlang language fundamentals - see lang-erlang-dev
• Haskell language fundamentals - see lang-haskell-dev
• Elixir conversions - see convert-elixir-haskell

---

Quick Reference

Erlang	Haskell	Notes
atom()	Data.Text or custom sum type	Atoms → Text or algebraic types
integer()	Integer or Int	Unbounded vs. bounded
float()	Double or Float	Precision choice
binary()	ByteString	Data.ByteString.Strict or .Lazy
list()	[a]	Homogeneous lists
tuple()	(a, b, ...) or custom product type	Fixed-size tuples or records
map()	Map k v	Data.Map.Strict
pid()	ThreadId or Async a	Process identifiers
reference()	IORef or TVar	Mutable references
fun()	a -> b	First-class functions
ok | {error, Reason}	Either Error a or Maybe a	Error handling

---

Type System Mapping

Primitives

Erlang	Haskell	Example Conversion
42	42 :: Integer	Integer literals
3.14	3.14 :: Double	Floating point
true	True :: Bool	Boolean
undefined	Nothing :: Maybe a	Absence of value
<<"hello">>	"hello" :: ByteString	Binary strings
'atom'	"atom" :: Text or Atom ADT	Symbolic constants

Collections

Erlang	Haskell	Notes
[1, 2, 3]	[1, 2, 3] :: [Int]	Linked lists
{ok, Value}	Right Value :: Either Error a	Success tuple
#{key => value}	Map.fromList [(key, value)]	Key-value maps
[H|T]	(h:t)	List pattern matching

Composite Types

Erlang	Haskell	Example
-record(user, {name, age}).	data User = User { userName :: Text, userAge :: Int }	Records
-type result() :: ok | {error, term()}.	data Result = Ok | Error String	Sum types
-spec add(integer(), integer()) -> integer().	add :: Int -> Int -> Int	Function signatures
-opaque handle().	newtype Handle = Handle Int	Opaque types

Process Types

Erlang Concept	Haskell Equivalent	Library
pid()	Async a	async package
gen_server	Custom type class + TVar	stm, async
supervisor	Supervisor	immortal, distributed-process
Message passing	Chan, TQueue, STM	stm, unagi-chan

---

Idiom Translation

Pattern: Pattern Matching

Erlang:

handle_result(ok) -> success;
handle_result({error, Reason}) -> {failure, Reason};
handle_result(Other) -> {unknown, Other}.

Haskell:

data Result = Ok | Error String
data Response = Success | Failure String | Unknown String

handleResult :: Result -> Response
handleResult Ok = Success
handleResult (Error reason) = Failure reason

Why this translation: Haskell's pattern matching is structurally similar but requires explicit type constructors in algebraic data types.

---

Pattern: Message Passing (gen_server)

Erlang:

-module(counter).
-behaviour(gen_server).

handle_call(increment, _From, State) ->
    {reply, ok, State + 1};
handle_call(get, _From, State) ->
    {reply, State, State}.

Haskell:

module Counter where

import Control.Concurrent.STM

data CounterMsg = Increment | Get (TMVar Int)

counter :: TVar Int -> CounterMsg -> STM ()
counter state Increment = modifyTVar' state (+1)
counter state (Get reply) = readTVar state >>= putTMVar reply

Why this translation: Haskell uses Software Transactional Memory (STM) instead of actor message passing. TVar provides lock-free mutable state.

---

Pattern: Supervision Trees

Erlang:

init([]) ->
    Children = [
        {worker1, {worker, start_link, []}, permanent, 5000, worker, [worker]}
    ],
    {ok, {{one_for_one, 5, 10}, Children}}.

Haskell:

import Control.Immortal

runSupervised :: IO ()
runSupervised = do
    thread <- createWithLabel "worker1" $ \_ -> worker
    onUnexpectedFinish thread $ \_ -> print "Worker crashed, restarting"

Why this translation: immortal library provides automatic restart semantics. For full OTP-style supervision, use distributed-process or cloud-haskell.

---

Pattern: Spawn and Message Send

Erlang:

Pid = spawn(fun() -> loop() end),
Pid ! {hello, self()},
receive
    {reply, Msg} -> io:format("Got: ~p~n", [Msg])
end.

Haskell:

import Control.Concurrent
import Control.Concurrent.Chan

spawnWorker :: IO ()
spawnWorker = do
    chan <- newChan
    replyChan <- newChan
    _ <- forkIO $ worker chan
    writeChan chan (Hello, replyChan)
    reply <- readChan replyChan
    putStrLn $ "Got: " ++ show reply

Why this translation: Haskell's Chan provides FIFO message queues. Use async for lightweight process management.

---

Pattern: List Comprehensions

Erlang:

Doubles = [X*2 || X <- [1,2,3,4], X rem 2 =:= 0].

Haskell:

doubles :: [Int]
doubles = [x*2 | x <- [1,2,3,4], even x]

Why this translation: Syntax is nearly identical. Haskell's comprehensions support multiple generators and guards.

---

Pattern: Error Handling

Erlang:

case file:read_file("data.txt") of
    {ok, Data} -> process(Data);
    {error, Reason} -> handle_error(Reason)
end.

Haskell:

import qualified Data.ByteString as BS
import Control.Exception

readAndProcess :: IO ()
readAndProcess = do
    result <- try (BS.readFile "data.txt") :: IO (Either IOError BS.ByteString)
    case result of
        Right dat -> process dat
        Left err -> handleError err

Why this translation: Haskell uses exception handling via try/catch or the Either monad. For pure code, prefer ExceptT transformer.

---

Pattern: Higher-Order Functions

Erlang:

lists:map(fun(X) -> X * 2 end, [1,2,3]).
lists:foldl(fun(X, Acc) -> X + Acc end, 0, [1,2,3]).

Haskell:

map (*2) [1,2,3]
foldl (+) 0 [1,2,3]

Why this translation: Haskell's curried functions eliminate need for explicit lambdas. Point-free style is idiomatic.

---

Pattern: Binary Pattern Matching

Erlang:

<<Version:8, Type:8, Payload/binary>> = Packet.

Haskell:

import qualified Data.Binary.Get as Get
import Data.ByteString.Lazy (ByteString)
import Data.Word (Word8)

parsePacket :: ByteString -> (Word8, Word8, ByteString)
parsePacket = Get.runGet $ do
    version <- Get.getWord8
    typ <- Get.getWord8
    payload <- Get.getRemainingLazyByteString
    return (version, typ, payload)

Why this translation: Haskell's binary package provides parsing combinators. cereal and attoparsec are alternatives.

---

Pattern: Guards

Erlang:

abs(X) when X < 0 -> -X;
abs(X) -> X.

Haskell:

abs' :: (Ord a, Num a) => a -> a
abs' x | x < 0     = -x
       | otherwise = x

Why this translation: Syntax nearly identical. Haskell guards use | instead of when.

---

Pattern: ETS Tables

Erlang:

Table = ets:new(cache, [set, public]),
ets:insert(Table, {key, value}),
[{key, Value}] = ets:lookup(Table, key).

Haskell:

import qualified Data.HashTable.IO as HT

type HashTable k v = HT.BasicHashTable k v

useCache :: IO ()
useCache = do
    table <- HT.new :: IO (HashTable String String)
    HT.insert table "key" "value"
    value <- HT.lookup table "key"
    print value

Why this translation: Mutable hash tables via hashtables package. For pure code, use Data.Map.

---

Error Handling

Philosophy Shift

Erlang: "Let it crash" - processes fail, supervisors restart them.
Haskell: "Make illegal states unrepresentable" - type system prevents errors at compile time.

Practical Translation

Erlang:

-spec divide(number(), number()) -> {ok, number()} | {error, divide_by_zero}.
divide(_, 0) -> {error, divide_by_zero};
divide(X, Y) -> {ok, X / Y}.

Haskell:

data DivideError = DivideByZero

divide :: Double -> Double -> Either DivideError Double
divide _ 0 = Left DivideByZero
divide x y = Right (x / y)

-- Or using Maybe for simpler errors
divide' :: Double -> Double -> Maybe Double
divide' _ 0 = Nothing
divide' x y = Just (x / y)

Exception Handling

Erlang:

try
    risky_operation()
catch
    error:Reason -> {error, Reason}
end.

Haskell:

import Control.Exception

safeRisky :: IO (Either SomeException Result)
safeRisky = try riskyOperation

---

Concurrency Patterns

1. Lightweight Processes

Erlang:

spawn(fun worker/0)

Haskell:

import Control.Concurrent.Async

async worker  -- Returns Async a

Pattern: Use async for fire-and-forget, race for first-to-finish, concurrently for parallel composition.

---

2. Message Channels

Erlang:

Pid ! Message,
receive Pattern -> handle(Pattern) end.

Haskell:

import Control.Concurrent.Chan

writeChan chan message
msg <- readChan chan

Alternatives:

• TQueue (STM-based, composable)
• unagi-chan (high-performance bounded channels)

---

3. Select-Style Multiplexing

Erlang:

receive
    {msg1, Data} -> handle_msg1(Data);
    {msg2, Data} -> handle_msg2(Data)
after 1000 ->
    timeout
end.

Haskell:

import Control.Concurrent.STM

selectMessage :: TQueue Msg1 -> TQueue Msg2 -> IO Response
selectMessage q1 q2 = atomically $
    (handleMsg1 <$> readTQueue q1) `orElse`
    (handleMsg2 <$> readTQueue q2)

Pattern: orElse provides non-deterministic choice. For timeouts, use registerDelay.

---

4. GenServer Equivalent

Erlang:

-module(kv_store).
-behaviour(gen_server).

-export([start_link/0, put/2, get/1]).
-export([init/1, handle_call/3, handle_cast/2]).

start_link() -> gen_server:start_link(?MODULE, [], []).
init([]) -> {ok, #{}}.

put(Pid, Key, Value) -> gen_server:cast(Pid, {put, Key, Value}).
get(Pid, Key) -> gen_server:call(Pid, {get, Key}).

handle_cast({put, Key, Value}, State) ->
    {noreply, State#{Key => Value}}.

handle_call({get, Key}, _From, State) ->
    {reply, maps:get(Key, State, undefined), State}.

Haskell:

module KVStore where

import Control.Concurrent.STM
import qualified Data.Map.Strict as Map

data KVStore k v = KVStore (TVar (Map.Map k v))

newKVStore :: STM (KVStore k v)
newKVStore = KVStore <$> newTVar Map.empty

put :: Ord k => KVStore k v -> k -> v -> STM ()
put (KVStore store) key value = modifyTVar' store (Map.insert key value)

get :: Ord k => KVStore k v -> k -> STM (Maybe v)
get (KVStore store) key = Map.lookup key <$> readTVar store

-- Usage:
-- store <- atomically newKVStore
-- atomically $ put store "key" "value"
-- value <- atomically $ get store "key"

---

5. Distributed Computing

Erlang:

{server, 'node@host'} ! Message.

Haskell (Cloud Haskell):

import Control.Distributed.Process

send serverId message

Libraries:

• distributed-process: Erlang-style distributed computing
• network-transport-tcp: Network backend
• cloud-haskell: Full framework

---

Memory & Ownership

Garbage Collection

Both Erlang and Haskell use GC, but differently:

Aspect	Erlang	Haskell
GC Strategy	Per-process generational	Generational for whole heap
Latency	Microsecond pauses per process	Millisecond pauses (tunable)
Memory Model	Process-local heaps	Shared heap with immutability
Tuning	spawn_opt flags	GHC RTS options (-H, -A)

Mutable State

Erlang:

% Processes hold mutable state via recursion
loop(State) ->
    receive
        {update, NewState} -> loop(NewState)
    end.

Haskell:

-- Explicit mutability via IORef or TVar
import Data.IORef

updateState :: IORef Int -> IO ()
updateState ref = modifyIORef' ref (+1)

Philosophy: Haskell makes mutation explicit in types (IO, STM). Pure functions remain referentially transparent.

---

Common Pitfalls

1. Forgetting Type Signatures

Problem: Haskell infers types, but polymorphism can cause ambiguity.

Solution: Always write top-level type signatures.

-- Bad: Type defaulting may surprise you
divide x y = x / y

-- Good: Explicit constraints
divide :: Double -> Double -> Double
divide x y = x / y

---

2. Overusing Exceptions in Pure Code

Problem: error, undefined break referential transparency.

Solution: Use Maybe, Either, or ExceptT.

-- Bad: Exception in pure code
head' [] = error "Empty list"

-- Good: Explicit failure
head' :: [a] -> Maybe a
head' [] = Nothing
head' (x:_) = Just x

---

3. Ignoring Laziness

Problem: Erlang is strict; Haskell is lazy. Space leaks possible.

Solution: Use strict data structures and functions when needed.

import qualified Data.Map.Strict as Map  -- Not Data.Map
import Data.List (foldl')                -- Not foldl

sum' :: [Int] -> Int
sum' = foldl' (+) 0  -- Strict accumulator

---

4. Blocking in STM

Problem: atomically blocks can cause deadlocks if misused.

Solution: Keep STM transactions short and pure.

-- Bad: IO inside STM (won't compile)
atomically $ do
    x <- readTVar var
    putStrLn "Debug"  -- ERROR!

-- Good: IO outside STM
x <- atomically $ readTVar var
putStrLn $ "Value: " ++ show x

---

5. Misunderstanding Monads

Problem: Treating IO like synchronous Erlang code.

Solution: Embrace do-notation and functors.

-- Haskell idiomatic
contents <- readFile "file.txt"
process contents

---

6. Not Using Newtype

Problem: Primitive obsession (using String, Int everywhere).

Solution: Wrap primitives for type safety.

-- Bad
type UserId = Int

-- Good
newtype UserId = UserId Int

---

7. Channel Deadlocks

Problem: Mixing Chan with synchronous expectations.

Solution: Use async for structured concurrency.

-- Prefer this over manual channel management
result <- async computation
wait result

---

8. Forgetting Stack/Cabal Configuration

Problem: Erlang's rebar3 manages deps; Haskell needs explicit config.

Solution: Use Stack or Cabal with curated package sets (Stackage).

# stack.yaml
resolver: lts-22.0
packages:
  - .
extra-deps: []

---

Tooling

Ecosystem Equivalents

Erlang Tool	Haskell Equivalent	Purpose
rebar3	stack or cabal	Build system
dialyzer	ghc -Wall -Werror	Static analysis
eunit	hspec or tasty	Unit testing
common_test	hspec + QuickCheck	Property testing
observer	threadscope, eventlog2html	Profiling
recon	ekg	Runtime monitoring
relx	docker + static binaries	Release management
hex	hackage / stackage	Package registry

Development Workflow

# Erlang
rebar3 new app myapp
rebar3 compile
rebar3 shell

# Haskell
stack new myapp
stack build
stack ghci

---

Migration Strategy

Step 1: Identify OTP Boundaries

• Map gen_server, gen_statem, supervisor to Haskell equivalents
• Document message protocols

Step 2: Translate Core Logic

• Start with pure functions (easiest to translate)
• Convert -spec to type signatures
• Port pattern matching and guards

Step 3: Replace Concurrency Primitives

• spawn → async
• receive → Chan or STM
• Supervision → immortal or distributed-process

Step 4: Handle Binary Protocols

• Use binary, cereal, or attoparsec
• Preserve wire format compatibility if needed

Step 5: Testing

• Port EUnit tests to Hspec
• Use QuickCheck for property-based testing
• Add type-driven tests (e.g., should-not-typecheck)

Step 6: Performance Tuning

• Profile with +RTS -p
• Use strict data structures
• Consider deepseq for forcing evaluation

Step 7: Deployment

• Build static binaries with stack --docker
• Use multi-stage Docker builds
• Consider GHC runtime flags (-N, -H, -A)

---

Examples

Example 1: Simple HTTP Client

Erlang:

-module(http_client).
-export([fetch/1]).

fetch(Url) ->
    inets:start(),
    case httpc:request(get, {Url, []}, [], []) of
        {ok, {{_, 200, _}, _, Body}} -> {ok, Body};
        {ok, {{_, Code, _}, _, _}} -> {error, Code};
        {error, Reason} -> {error, Reason}
    end.

Haskell:

module HttpClient where

import Network.HTTP.Simple
import qualified Data.ByteString.Lazy.Char8 as L8

fetch :: String -> IO (Either String String)
fetch url = do
    response <- httpLBS (parseRequest_ url)
    let status = getResponseStatusCode response
    return $ if status == 200
        then Right (L8.unpack $ getResponseBody response)
        else Left ("HTTP " ++ show status)

---

Example 2: Concurrent File Processing

Erlang:

process_files(Files) ->
    Parent = self(),
    [spawn(fun() ->
        {ok, Data} = file:read_file(F),
        Parent ! {done, F, process(Data)}
     end) || F <- Files],
    collect(length(Files), []).

collect(0, Acc) -> Acc;
collect(N, Acc) ->
    receive {done, File, Result} -> collect(N-1, [{File, Result}|Acc]) end.

Haskell:

import Control.Concurrent.Async
import qualified Data.ByteString as BS

processFiles :: [FilePath] -> IO [(FilePath, Result)]
processFiles files =
    forConcurrently files $ \file -> do
        dat <- BS.readFile file
        let result = process dat
        return (file, result)

---

Example 3: GenServer-Style State Machine

Erlang:

-module(door).
-behaviour(gen_statem).

locked(cast, {button, Code}, #{code := Code} = Data) ->
    {next_state, unlocked, Data};
locked(cast, {button, _}, Data) ->
    {keep_state, Data}.

unlocked(cast, lock, Data) ->
    {next_state, locked, Data}.

Haskell:

{-# LANGUAGE LambdaCase #-}

module Door where

import Control.Concurrent.STM

data State = Locked | Unlocked
data Event = Button Int | Lock

doorFSM :: TVar State -> Int -> Event -> STM ()
doorFSM state correctCode = \case
    Button code | code == correctCode -> writeTVar state Unlocked
    Button _ -> return ()
    Lock -> writeTVar state Locked

---

See Also

• lang-erlang-dev: Erlang development patterns and OTP design
• lang-haskell-dev: Haskell idioms, type-level programming, monad transformers
• meta-convert-dev: General principles for language translation
• convert-elixir-haskell: Similar conversion for Elixir (BEAM) to Haskell