Use when writing or reviewing Kotlin StateFlow/SharedFlow/Channel choices, sentinel default values, stateIn placement, WhileSubscribed staleness, or MutableStateFlow update patterns. Technique-layer skill — complements the codebase-specific kotlin-expert.
Kotlin Flow: state and event modeling
Core principle
Pick the primitive that matches replay, fan-out, and synchronous-read requirements.StateFlow, SharedFlow, Channel-backed flows, and cold Flow differ in buffering, who sees each emission, and whether .value exists. Wrong choices drop events, leak sharing coroutines, or force fake domain sentinels into state.
When to use this skill
You're writing or reviewing Kotlin code involving:
MutableStateFlow<T>(SomeSentinel) — NoUser, Empty, Loading, etc. — because the real value is async
.stateIn(...) called inside a function rather than assigned to a property
SharingStarted.WhileSubscribed(...) on a flow whose .value is read synchronously and must stay fresh
MutableSharedFlow for navigation events, snackbars, or other one-shot emissions where loss would be a bug
.map { } on a StateFlow when consumers still need synchronous .value
MutableStateFlow.value = _state.value.copy(...) or update code that builds expensive objects inside update { ... }
SharedFlow for single-consumer fire-once events
SharedFlow defaults have no replay buffer. If nothing is collecting at the exact instant of emission, the event is gone. For a handling exactly-once events such as navigation or snackbars, a buffered exposed as a often matches the semantics better:
Channel.receiveAsFlow() is fan-out, not broadcast: with multiple collectors, each event is delivered to one collector. Channel.BUFFERED is bounded, so sends can suspend and trySend can fail. If multiple observers must all see the same event, use explicit state, durable storage, or a deliberately configured SharedFlow instead.
StateFlow polluted with invalid sentinel defaults
StateFlow forces an initial value. When the real value is async, developers sometimes invent fake domain values — NoUser, EmptyUser, placeholder IDs — and every consumer is forced to treat that sentinel as real data.
// ❌ BAD — sentinel leaks into the typeclassUserSession(privateval db: Db) {
privateval _user = MutableStateFlow<User>(NoUser)
val user: StateFlow<User> = _user.asStateFlow()
init { scope.launch { _user.value = db.load() } }
}
One fix is phasing: don't expose the StateFlow until the real value exists.
// ✅ GOOD — bootstrap suspends; observers only see real usersclassUserSession(privateval db: Db) {
privatevar _user: MutableStateFlow<User>? = nullval user: StateFlow<User>
get() = checkNotNull(_user) { "Call login() first" }
suspendfunlogin() {
_user = MutableStateFlow(db.load())
}
}
If absence, loading, or error is a real state, model it explicitly (User?, sealed interface UserUiState, Result, etc.). The bug is a fake domain value masquerading as real data, not every initial value.
Mutate MutableStateFlow with update { ... }
Prefer MutableStateFlow.update { current -> ... } over reading .value and writing it back. update applies the transform atomically against the latest state, which avoids lost updates when multiple coroutines mutate the same state.
// BAD — read/modify/write can lose concurrent updates.
_state.value = _state.value.copy(
selectedId = id,
details = details,
)
// GOOD — transform starts from the latest state.
_state.update { current ->
current.copy(
selectedId = id,
details = details,
)
}
Keep object creation outside the update block unless it needs the current state. The update lambda can be retried, so expensive work or side effects inside it may run more than once:
// GOOD — details does not depend on current state, so build it once.val details = Details.from(response)
_state.update { current ->
current.copy(details = details)
}
// GOOD — derived value depends on current state, so compute it inside.
_state.update { current ->
val nextItems = current.items.replaceById(updatedItem)
current.copy(items = nextItems)
}
The block should be a pure, fast state transformation: no network calls, database writes, logging side effects, random IDs, or time reads unless those values were captured before the block.
stateIn() inside a function
// ❌ BAD — new sharing coroutine every callfungetPreferences(): StateFlow<Prefs> =
repo.prefsFlow.stateIn(scope, SharingStarted.Eagerly, Prefs.Default)
Every call to getPreferences() launches a fresh coroutine on scope that never completes. Performance dies fast under repeated reads.
// ✅ GOOD — one shared instance, computed onceval preferences: StateFlow<Prefs> =
repo.prefsFlow.stateIn(viewModelScope, SharingStarted.Eagerly, Prefs.Default)
WhileSubscribed with synchronous .value
SharingStarted.WhileSubscribed(timeout) disconnects the upstream when there are no active collectors. While disconnected, .value returns the last cached value, which may be stale or still the initial value.
Rule: if .value must be fresh or initialized without an active collector, use SharingStarted.Eagerly or explicit initialization. WhileSubscribed is fine when stale/cached values are acceptable and consumers primarily collect asynchronously.
.map on StateFlow loses .value
// ❌ BAD — `name.value` won't compile; it's now a plain Flowval name: Flow<String> = userState.map { it.name }
If you need synchronous .value, terminate the chain with .stateIn(...):
Community "derived state flow" utilities run the transform on every .value read — only acceptable for fast, idempotent transforms. Default to .stateIn(...).
Decision: which Flow type?
Need
Primitive
State that always has a value, read by both async collectors and synchronous code
StateFlow, often with SharingStarted.Eagerly when .value matters
Hot stream, multiple subscribers, no requirement for synchronous .value
SharedFlow
Discrete events for one consumer, exactly-once handoff
Consider Channel(BUFFERED).receiveAsFlow()
Cold stream, one consumer per collection
Plain Flow
If you're tempted to reach for SharedFlow, ask: would dropping an emission be a bug, and how many consumers must see it? If one consumer must handle it exactly once, a Channel may fit. If every observer must see it, model durable state or configure a broadcast stream deliberately.
Quick reference
Symptom
Problem
Fix
MutableStateFlow<X>(FakeDomainValue)
Invalid placeholder default
Model absence explicitly or use phase initialization
MutableSharedFlow<Event> for single-consumer nav/snackbar
Lossy default event stream
Consider Channel(BUFFERED).receiveAsFlow()
fun foo() = flow.stateIn(...)
Per-call sharing coroutine
Make it a val / shared instance
WhileSubscribed + .value must be fresh/initialized
Stale or initial data
SharingStarted.Eagerly or explicit initialization
stateFlow.map { ... } consumed as state
Lost .value
Terminate with .stateIn(...)
_state.value = _state.value.copy(...)
Non-atomic read/modify/write
_state.update { it.copy(...) }
Expensive object creation inside update { ... } that doesn't use current state
Work can repeat if update retries
Build before update; keep only current-state transforms inside
Red flags during review
Thought
Reality
"We need SharedFlow because there are multiple subscribers"
Multiple subscribers change the semantics. Channel.receiveAsFlow() is not broadcast; choose the event model deliberately.
"We'll use WhileSubscribed to save resources"
Only if stale/initial .value reads are acceptable. Verify before applying.
"I'll use a sentinel until real data loads"
Consumers treat it as real domain; prefer explicit UI/state modeling or phasing.
"I'll construct the new object inside update because it's convenient"
The lambda may retry. Construct outside unless it depends on the current state.
