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npx skills add https://github.com/prasad-vennam/awesome-android-ai-agent-skills --skill android-macrobenchmarkPrima di iniziare
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Android Macrobenchmark & Baseline Profiles 🏎️
App Startup Time and UI performance are crucial. Macrobenchmark allows us to write standard JUnit 4 tests to measure end-to-end user journeys (like app startup or scrolling a list) and automatically generate Baseline Profiles that Android's ART uses to pre-compile critical code.
⚡ When to Use
- When the prompt mentions "speeding up app startup time"
- When writing a Macrobenchmark module
- When generating or applying Baseline Profiles (
baseline-prof.txt)
🏗️ Core Rules / Pillars
1. Separate Macrobenchmark Module
- Pattern: Macrobenchmarks MUST be in a separate
com.android.testmodule. They launch your application by itsapplicationIdexternally. - Anti-Pattern: Do NOT attempt to run Macrobenchmark tests inside the standard
app/src/androidTestdirectory.
2. Writing a Scrolling Benchmark
- Implementation:
@RunWith(AndroidJUnit4::class)
class ScrollBenchmark {
@get:Rule
val benchmarkRule = MacrobenchmarkRule()
@Test
fun scrollTimeline() = benchmarkRule.measureRepeated(
packageName = "com.example.app",
metrics = listOf(FrameTimingMetric()),
iterations = 5,
startupMode = StartupMode.COLD
) {
pressHome()
startActivityAndWait()
// Using UIAutomator to find the scrollable list and scroll
val list = device.findObject(By.res("com.example.app", "timeline_list"))
list.setGestureMargin(device.displayWidth / 5)
list.fling(Direction.DOWN)
}
}🚧 Critical Anti-Hallucination Guards
- Trap: Baseline Profiles generation requires a rooted device OR a device running Android 13 (API 33)+.


