Files
wickra/fuzz/fuzz_targets/indicator_update_candle.rs
T
kingchenc e043a0dd9b feat(ao-histogram): add Awesome Oscillator Histogram
AO - SMA(AO, sma_period). A configurable variant of the existing
AcceleratorOscillator (which fixes fast=5, slow=34, sma=5).
Three parameters; defaults match Bill Williams' Accelerator.

Touchpoints: awesome_oscillator_histogram.rs + mod.rs + lib.rs
re-export, PyAoHist + __init__.py + test_new_indicators CANDLE_SCALAR
+ test_known_values flat reference, AwesomeOscillatorHistogramNode +
index.d.ts/index.js + indicators.test.js factory + reference,
WasmAoHist, candle-fuzz target, README + CHANGELOG.
2026-05-24 21:43:26 +02:00

136 lines
5.7 KiB
Rust

#![no_main]
//! Fuzz OHLCV-input indicator updates with arbitrary candle sequences.
//!
//! Every candle-input indicator must tolerate any sequence of validated OHLCV
//! candles — extreme magnitudes, micro-spreads, zero-volume bars, abrupt
//! reversals — without panicking. The fuzzer chunks the raw `f64` stream into
//! `[open, high, low, close, volume]` tuples and constructs each candle via
//! `Candle::new`; entries that fail OHLCV-invariant validation are skipped so
//! the indicator only ever sees structurally-valid candles. Each iteration
//! then drives that candle stream through every candle-input indicator twice
//! (streaming `update` + batch).
//!
//! Audit finding R9: the previous fuzz suite had no candle-input coverage at
//! all. This target now covers every candle-input indicator including the
//! ones the audit named explicitly (ATR, ADX, Stochastic, PSAR) plus the
//! complete catalogue: Keltner, Donchian, SuperTrend, Chandelier Exit, ATR
//! Trailing Stop, Aroon, AwesomeOscillator, CCI, WilliamsR, MFI, OBV, VWAP,
//! RollingVWAP, ADL, VPT, ChaikinMoneyFlow, ChaikinOscillator, ForceIndex,
//! EaseOfMovement, NATR, AroonOscillator, ChandeKrollStop, Vortex, MassIndex,
//! ChoppinessIndex, TrueRange, ChaikinVolatility, AcceleratorOscillator,
//! BalanceOfPower, UltimateOscillator, VWMA, TypicalPrice, MedianPrice,
//! WeightedClose.
use libfuzzer_sys::fuzz_target;
use wickra_core::{
AcceleratorOscillator, Adl, Adx, Aroon, AroonOscillator, Atr, AtrTrailingStop,
AwesomeOscillator, AwesomeOscillatorHistogram, BalanceOfPower, BatchExt, Candle, Cci,
ChaikinMoneyFlow, ChaikinOscillator,
ChaikinVolatility, ChandeKrollStop, ChandelierExit, ChoppinessIndex, Donchian, EaseOfMovement,
ForceIndex, Indicator, Keltner, MassIndex, MedianPrice, Mfi, Natr, Obv, Psar, RollingVwap,
Stochastic, SuperTrend, TrueRange, TypicalPrice, UltimateOscillator, VolumePriceTrend, Vortex,
Vwap, Vwma, WeightedClose, WilliamsR,
};
/// Convert a flat `f64` stream into a `Vec<Candle>` by chunking it into
/// `[open, high, low, close, volume]` groups. Tuples that fail OHLCV
/// validation are dropped so the indicator under test only ever sees a
/// structurally-valid candle stream (the *parser* is fuzz-tested elsewhere;
/// this target focuses on indicator robustness).
fn candles_from(data: &[f64]) -> Vec<Candle> {
data.chunks_exact(5)
.enumerate()
.filter_map(|(i, ch)| {
// A monotonic timestamp avoids surprising any indicator that might
// care about ordering. The fuzz input drives OHLCV; time is just a
// tie-breaker.
Candle::new(ch[0], ch[1], ch[2], ch[3], ch[4], i as i64).ok()
})
.collect()
}
/// Streaming + batch sweep through one candle-input indicator. `#[inline(never)]`
/// keeps each indicator on its own frame in any panic backtrace.
#[inline(never)]
fn drive<I, O>(make: impl Fn() -> I, candles: &[Candle])
where
I: Indicator<Input = Candle, Output = O> + BatchExt,
{
let mut streaming = make();
for c in candles {
let _ = streaming.update(*c);
}
let _ = make().batch(candles);
}
fuzz_target!(|data: Vec<f64>| {
let candles = candles_from(&data);
if candles.is_empty() {
return;
}
// --- Volatility & ATR family ---
drive(|| Atr::new(14).unwrap(), &candles);
drive(|| Natr::new(14).unwrap(), &candles);
drive(TrueRange::new, &candles);
drive(|| ChaikinVolatility::new(10, 10).unwrap(), &candles);
// --- Bands & Channels ---
drive(|| Keltner::new(20, 10, 2.0).unwrap(), &candles);
drive(|| Donchian::new(20).unwrap(), &candles);
// --- Trailing Stops ---
drive(|| Psar::new(0.02, 0.02, 0.20).unwrap(), &candles);
drive(|| SuperTrend::new(14, 3.0).unwrap(), &candles);
drive(|| ChandelierExit::new(22, 3.0).unwrap(), &candles);
drive(|| ChandeKrollStop::new(10, 1.0, 9).unwrap(), &candles);
drive(|| AtrTrailingStop::new(14, 3.0).unwrap(), &candles);
// --- Trend & Directional ---
drive(|| Adx::new(14).unwrap(), &candles);
drive(|| Aroon::new(14).unwrap(), &candles);
drive(|| AroonOscillator::new(14).unwrap(), &candles);
drive(|| Vortex::new(14).unwrap(), &candles);
drive(|| MassIndex::new(9, 25).unwrap(), &candles);
drive(|| ChoppinessIndex::new(14).unwrap(), &candles);
// --- Momentum & Oscillators ---
drive(|| Cci::new(20).unwrap(), &candles);
drive(|| WilliamsR::new(14).unwrap(), &candles);
drive(|| AwesomeOscillator::new(5, 34).unwrap(), &candles);
drive(
|| AwesomeOscillatorHistogram::new(5, 34, 5).unwrap(),
&candles,
);
drive(|| AcceleratorOscillator::new(5, 34, 5).unwrap(), &candles);
drive(|| UltimateOscillator::new(7, 14, 28).unwrap(), &candles);
drive(BalanceOfPower::new, &candles);
// --- Volume ---
drive(Obv::new, &candles);
drive(|| Mfi::new(14).unwrap(), &candles);
drive(Vwap::new, &candles);
drive(|| RollingVwap::new(20).unwrap(), &candles);
drive(|| Vwma::new(20).unwrap(), &candles);
drive(Adl::new, &candles);
drive(VolumePriceTrend::new, &candles);
drive(|| ChaikinMoneyFlow::new(20).unwrap(), &candles);
drive(|| ChaikinOscillator::new(3, 10).unwrap(), &candles);
drive(|| ForceIndex::new(13).unwrap(), &candles);
drive(|| EaseOfMovement::with_divisor(14, 1e8).unwrap(), &candles);
// --- Price transformations ---
drive(TypicalPrice::new, &candles);
drive(MedianPrice::new, &candles);
drive(WeightedClose::new, &candles);
// --- Stochastic (multi-output) ---
{
let mut s = Stochastic::new(14, 3).unwrap();
for c in &candles {
let _ = s.update(*c);
}
let _ = Stochastic::new(14, 3).unwrap().batch(&candles);
}
});