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Folio
A minimal Kotlin Multiplatform personal-ledger app: login with demo credentials, create accounts, add credits and debits. Shared UI across Android, iOS, and web (wasmJs via Compose for Web). Doubles as the example sanderling runs its property-based specs against.
Stack
- Kotlin Multiplatform + Compose Multiplatform (shared UI)
- SQLDelight for the data layer (unified across platforms)
- kotlinx.coroutines for state flows
- kotlinx.serialization for
@Serializableroute types
Prerequisites
just- JDK 17
- Android SDK (auto-discovered under
$ANDROID_HOME,~/Library/Android/sdk, or the Homebrew cask) - Xcode 16+ and
xcodegen(brew install xcodegen) for iOS
Android
just install # build + install on a booted emulator / device
just uninstall
just clean
iOS
just ios # default device: iPhone 17 Pro
IOS_DEVICE="iPhone 15" just ios # pick a different simulator
just ios regenerates app/iosApp/iosApp.xcodeproj from app/iosApp/project.yml,
builds the KMP framework (Shared.framework from :app:shared), links it
into the SwiftUI host, installs, and launches.
Web
just web # webpack dev server with COOP/COEP headers
just web-build # produce a webpack distributable bundle
just web runs :app:webApp:wasmJsBrowserDevelopmentRun --continuous, so
edits to shared code reload in the browser.
Demo credentials
email: [email protected]
password: ledger123
Run a sanderling test (Android)
just test
If no device is connected, sanderling boots the single AVD it finds. With multiple AVDs, pick one:
AVD=Pixel_7 just test
Persistent settings can live in .env alongside the justfile:
AVD=Pixel_7
DURATION=5m
Traces land in ./sanderling/runs/<timestamp>/.
Run with the LLM action generator
The same sanderling/spec.ts runs under either generator: --generator seeded
(the default weighted fuzzer) or --generator llm, where a vision model picks
from the SAME weighted candidate set (reading the screenshot plus a numbered,
weight-annotated list of concrete actions) and returns one number. The spec's
generator = llm({ model, instructions }) export configures it.
export OPENROUTER_API_KEY=sk-or-... # or OPENAI_API_KEY=sk-... for OpenAI direct
just test-llm # or: sanderling test --generator llm --spec sanderling/spec.ts --bundle-id app.folio
OpenRouter wins when both keys are set. With a plain OpenAI key, drop the vendor
prefix from the model id in spec.ts (gpt-5.4-nano, not
openai/gpt-5.4-nano). The model must support image input and strict
json_schema structured outputs. Each step is one multimodal call, so keep the
duration / step budget modest. The trace records the model's reasoning, the
chosen number, and source: "llm" on each action, so the replay UI shows why
each pick was made.
Run a sanderling test (iOS)
just test-ios # default simulator: iPhone 17 Pro
IOS_DEVICE="iPhone 15" just test-ios # pick a different simulator
just test-ios boots the simulator if needed, runs just ios to install
and launch the app, then invokes sanderling test --platform ios. Same
DURATION, SEED, and OUTPUT env vars as the Android target.
How it connects to sanderling
- Each screen sets a stable Compose
testTag(HomeScreen,AccountCard,LedgerRow,TxnAmount, ...). The Sanderling SDK resolvestestTagtoresource-idon Android andaccessibilityIdentifieron iOS. - Identity for list items is the visible text content (account name; txn note + amount). No synthetic IDs encoded in semantics.
contentDescriptionis reserved for real accessibility labels, never as a data carrier.sanderling/spec.tsimports@sanderling/spec, reads state vias.ax.*, asserts properties, and weights the actions the fuzzer picks from.just testinvokessanderling testagainst the installed APK.