Compose Multiplatform Performance Optimization Guide

Building apps that feel fast across all platforms is like cooking the perfect steak – get the timing wrong by just a few seconds and the whole experience suffers. Compose Multiplatform gives us incredible power to share UI code, but without proper lifecycle management and performance tuning, your app might run like a smartphone from 2008.

After optimizing dozens of cross-platform apps, I’ve learned that the secret sauce involves understanding three things: when your UI loads, how it updates, and when it cleans up after itself. Let’s break down how to get this right on every platform.

Lifecycle Events Across Platforms

Each platform handles lifecycles differently. Here’s what matters most:

Platform	Key Moments	Watch Out For
Android	onCreate/onStart/onResume	Configuration changes
iOS	viewDidLoad/viewWillAppear	Background refreshes
Desktop	window opening/closing	Multiple windows
Web	DOM mount/unmount	Tab visibility changes

Here’s how to handle a common scenario – pausing video playback when the app backgrounds:

@Composable
fun VideoPlayer(url: String) {
    var isPlaying by remember { mutableStateOf(true) }
    val lifecycleOwner = LocalLifecycleOwner.current

    DisposableEffect(lifecycleOwner) {
        val observer = LifecycleEventObserver { _, event ->
            isPlaying = event.isAtLeast(Lifecycle.State.STARTED)
        }

        lifecycleOwner.lifecycle.addObserver(observer)

        onDispose {
            lifecycleOwner.lifecycle.removeObserver(observer)
        }
    }

    VideoComponent(url, isPlaying)
}

Performance Optimization Techniques

1. Smart List Rendering

Lazy lists are great until they’re not. Here’s how to optimize:

@Composable
fun MessageList(messages: List<Message>) {
    LazyColumn {
        items(messages, key = { it.id }) { message ->
            // Content stays stable if message doesn't change
            MessageItem(message) 
        }
    }
}

Key things to remember:

• Always provide stable keys
• Keep item composables lightweight
• Use derivedStateOf for complex transformations

2. Expensive Operations Done Right

Need to process images or do heavy calculations? Here’s the pattern:

@Composable
fun ImageProcessor(input: Image) {
    val processedImage by remember(input) {
        derivedStateOf {
            // This runs on a background thread
            withContext(Dispatchers.Default) {
                applyFilters(input)
            }
        }
    }

    Image(processedImage)
}

State Management That Scales

Poor state management is where most performance issues begin. Here’s a comparison of approaches:

Technique	Best For	Performance Impact
remember	UI-only state	Minimal
ViewModel	Screen-level state	Moderate
StateFlow	App-wide state	Needs careful use
Redux	Complex apps	Higher overhead

Here’s how I structure state in production apps:

class ConversationViewModel : ViewModel() {
    private val _messages = MutableStateFlow<List<Message>>(emptyList())
    val messages: StateFlow<List<Message>> = _messages

    fun loadConversation() {
        viewModelScope.launch {
            _messages.value = repository.loadMessages()
        }
    }
}

@Composable
fun ConversationScreen(viewModel: ConversationViewModel = viewModel()) {
    val messages by viewModel.messages.collectAsState()

    LaunchedEffect(Unit) {
        viewModel.loadConversation()
    }

    MessageList(messages)
}

Platform-Specific Optimizations

Each platform has unique optimization opportunities:

Android

• Use rememberCoroutineScope for lifecycle-aware coroutines
• Implement onTrimMemory callbacks

iOS

• Optimize for background app refresh
• Handle memory warnings properly

Desktop

• Manage multiple window states
• Optimize for keyboard/mouse input

Web

• Implement virtual scrolling
• Optimize for browser repaints

Here’s how to handle platform-specific optimizations:

expect fun getPlatformSpecificCacheSize(): Long

@Composable
expect fun PlatformPerformanceMonitor(): Unit

// Android implementation
actual fun getPlatformSpecificCacheSize(): Long {
    return Runtime.getRuntime().maxMemory() / 4
}

Debugging Performance Issues

When things get slow, here’s my debugging toolkit:

1. Compose Debugger – Identify recomposition counts
2. CPU Profiler – Find hot spots
3. Memory Analyzer – Catch leaks
4. StrictMode – Detect main thread violations

Add this to catch issues early:

@Composable
fun DebugPerformance() {
    if (LocalInspectionMode.current) {
        SideEffect {
            // Debugging code here
        }
    }
}

Testing Performance

Automated performance tests save headaches later:

@Test
fun messageListPerformance() = runComposeTest {
    val testMessages = List(1000) { Message("Test $it") }

    setContent {
        MessageList(testMessages)
    }

    onNodeWithTag("MessageList")
        .assertIsDisplayed()
        .assertRecompositionCount(lessThan(3))
}

Final Checklist

Before shipping your app, verify:

1. Lifecycle events are handled on all platforms
2. Heavy work happens off the main thread
3. Lists use keys and stable item types
4. State updates are minimal and batched
5. Platform-specific optimizations are in place

Remember, good performance isn’t about fancy tricks – it’s about doing the right work at the right time. Get this right, and your users will enjoy an app that feels fast and responsive everywhere.