Introduction

Rebound

Rebound is a Compose recomposition budget monitor. It assigns each @Composable function a recomposition rate budget based on what that composable does, and alerts you when the budget is exceeded.

A HomeScreen recomposing 10 times per second is a problem. A gesture-driven composable recomposing 10 times per second is fine. Same number, completely different situation. Flat thresholds cannot distinguish them. Rebound can.

Quick Start

Three lines in your build file:

build.gradle.kts

plugins {
    id("io.github.aldefy.rebound") version "0.1.0"
}

That is the entire setup. The Gradle plugin detects your Kotlin version, adds the correct compiler artifact, and injects the runtime as a debugImplementation dependency. No annotations, no wrapping functions, no code changes.

Run your app in debug mode. When a composable exceeds its budget, you will see:

W/Rebound: [VIOLATION] HomeScreen — 8 recomp/s (budget: 3, class: SCREEN)
  -> params: items=DIFFERENT, query=SAME
  -> forced: 0 | param-driven: 8 | interaction: IDLE

What Makes Rebound Different

The Compose ecosystem has solid tooling for recomposition analysis. Each tool answers a specific question well:

Tool	Question It Answers	Gap
Compose Compiler Reports	Can this composable be skipped?	Static analysis only, no runtime rates
Layout Inspector	How many times did this recompose?	Counts without context — 847 means nothing alone
Rebugger	What argument changed?	Manual per-composable setup, does not scale
ComposeInvestigator	Why did this recompose?	Tells the cause, not whether the rate is healthy
VKompose	Which composables are hot right now?	Visual highlighting, not rate-based analysis
Perfetto	Is the main thread janking?	Too heavy for “is this composable recomposing too much?”

Rebound answers the question none of them address: “Given what this composable does, is this recomposition rate acceptable?”

Key capabilities

• 7 budget classes — SCREEN (3/s), LEAF (5/s), CONTAINER (10/s), INTERACTIVE (30/s), LIST_ITEM (60/s), ANIMATED (120/s), UNKNOWN (30/s)
• Automatic classification — compiler plugin infers budgets from IR structure, zero config
• $changed bitmask decoding — surfaces which parameters caused each recomposition
• Interaction-aware scaling — budgets adjust during scroll, animation, and user input
• IDE plugin — live monitoring, hot spots, timeline heatmap, stability analysis, gutter icons
• CLI — snapshot, summary, watch, ping commands over ADB socket
• KMP — Android, JVM, iOS (arm64, x64, simulator arm64), Wasm
• Debug-only by default — zero overhead in release builds