TracingStage
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b28306519f
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@ -1,142 +1,54 @@
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use core::{marker::PhantomData, mem::drop};
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use crate::{
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bolts::rands::Rand,
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corpus::Corpus,
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fuzzer::Evaluator,
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executors::{Executor, HasExecHooks, HasExecHooksTuple, HasObservers, HasObserversHooks},
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inputs::Input,
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mark_feature_time,
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mutators::Mutator,
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observers::ObserversTuple,
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stages::Stage,
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start_timer,
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state::{HasClientPerfStats, HasCorpus, HasRand},
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state::{HasClientPerfStats, HasCorpus, HasExecutions},
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Error,
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};
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#[cfg(feature = "introspection")]
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use crate::stats::PerfFeature;
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// TODO multi mutators stage
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/// A Mutational stage is the stage in a fuzzing run that mutates inputs.
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/// Mutational stages will usually have a range of mutations that are
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/// being applied to the input one by one, between executions.
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pub trait TracingStage<C, E, EM, I, M, S, Z>: Stage<E, EM, S, Z>
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where
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C: Corpus<I>,
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M: Mutator<I, S>,
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I: Input,
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S: HasClientPerfStats + HasCorpus<C, I>,
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Z: Evaluator<E, EM, I, S>,
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{
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/// The mutator registered for this stage
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fn mutator(&self) -> &M;
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/// The mutator registered for this stage (mutable)
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fn mutator_mut(&mut self) -> &mut M;
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/// Gets the number of iterations this mutator should run for.
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fn iterations(&self, state: &mut S) -> usize;
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/// Runs this (mutational) stage for the given testcase
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#[allow(clippy::cast_possible_wrap)] // more than i32 stages on 32 bit system - highly unlikely...
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fn perform_mutational(
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&mut self,
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fuzzer: &mut Z,
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executor: &mut E,
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state: &mut S,
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manager: &mut EM,
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corpus_idx: usize,
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) -> Result<(), Error> {
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let num = self.iterations(state);
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for i in 0..num {
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start_timer!(state);
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let mut input = state
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.corpus()
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.get(corpus_idx)?
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.borrow_mut()
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.load_input()?
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.clone();
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mark_feature_time!(state, PerfFeature::GetInputFromCorpus);
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start_timer!(state);
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self.mutator_mut().mutate(state, &mut input, i as i32)?;
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mark_feature_time!(state, PerfFeature::Mutate);
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// Time is measured directly the `evaluate_input` function
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let (_, corpus_idx) = fuzzer.evaluate_input(state, executor, manager, input)?;
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start_timer!(state);
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self.mutator_mut().post_exec(state, i as i32, corpus_idx)?;
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mark_feature_time!(state, PerfFeature::MutatePostExec);
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}
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Ok(())
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}
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}
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/// Default value, how many iterations each stage gets, as an upper bound
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/// It may randomly continue earlier.
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pub static DEFAULT_MUTATIONAL_MAX_ITERATIONS: u64 = 128;
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/// The default mutational stage
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#[derive(Clone, Debug)]
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pub struct StdMutationalStage<C, E, EM, I, M, R, S, Z>
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pub struct TracingStage<C, EM, I, OT, S, TE, Z>
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where
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C: Corpus<I>,
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M: Mutator<I, S>,
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I: Input,
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R: Rand,
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S: HasClientPerfStats + HasCorpus<C, I> + HasRand<R>,
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Z: Evaluator<E, EM, I, S>,
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C: Corpus<I>,
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TE: Executor<I>
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+ HasObservers<OT>
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+ HasExecHooks<EM, I, S, Z>
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+ HasObserversHooks<EM, I, OT, S, Z>,
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OT: ObserversTuple + HasExecHooksTuple<EM, I, S, Z>,
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S: HasClientPerfStats + HasExecutions + HasCorpus<C, I>,
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{
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mutator: M,
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tracer_executor: TE,
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#[allow(clippy::type_complexity)]
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phantom: PhantomData<(C, E, EM, I, R, S, Z)>,
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phantom: PhantomData<(C, EM, I, OT, S, TE, Z)>,
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}
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impl<C, E, EM, I, M, R, S, Z> MutationalStage<C, E, EM, I, M, S, Z>
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for StdMutationalStage<C, E, EM, I, M, R, S, Z>
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impl<E, C, EM, I, OT, S, TE, Z> Stage<E, EM, S, Z> for TracingStage<C, EM, I, OT, S, TE, Z>
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where
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C: Corpus<I>,
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M: Mutator<I, S>,
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I: Input,
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R: Rand,
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S: HasClientPerfStats + HasCorpus<C, I> + HasRand<R>,
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Z: Evaluator<E, EM, I, S>,
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{
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/// The mutator, added to this stage
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#[inline]
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fn mutator(&self) -> &M {
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&self.mutator
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}
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/// The list of mutators, added to this stage (as mutable ref)
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#[inline]
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fn mutator_mut(&mut self) -> &mut M {
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&mut self.mutator
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}
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/// Gets the number of iterations as a random number
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fn iterations(&self, state: &mut S) -> usize {
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1 + state.rand_mut().below(DEFAULT_MUTATIONAL_MAX_ITERATIONS) as usize
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}
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}
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impl<C, E, EM, I, M, R, S, Z> Stage<E, EM, S, Z> for StdMutationalStage<C, E, EM, I, M, R, S, Z>
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where
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C: Corpus<I>,
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M: Mutator<I, S>,
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I: Input,
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R: Rand,
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S: HasClientPerfStats + HasCorpus<C, I> + HasRand<R>,
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Z: Evaluator<E, EM, I, S>,
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TE: Executor<I>
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+ HasObservers<OT>
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+ HasExecHooks<EM, I, S, Z>
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+ HasObserversHooks<EM, I, OT, S, Z>,
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OT: ObserversTuple + HasExecHooksTuple<EM, I, S, Z>,
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S: HasClientPerfStats + HasExecutions + HasCorpus<C, I>,
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{
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#[inline]
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fn perform(
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&mut self,
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fuzzer: &mut Z,
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executor: &mut E,
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_executor: &mut E,
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state: &mut S,
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manager: &mut EM,
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corpus_idx: usize,
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@ -161,7 +73,7 @@ where
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mark_feature_time!(state, PerfFeature::PreExec);
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start_timer!(state);
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drop(self.tracer_executor.run_target(&input)?);
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let _ = self.tracer_executor.run_target(&input)?;
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mark_feature_time!(state, PerfFeature::TargetExecution);
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start_timer!(state);
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@ -180,19 +92,21 @@ where
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}
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}
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impl<C, E, EM, I, M, R, S, Z> StdMutationalStage<C, E, EM, I, M, R, S, Z>
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impl<C, EM, I, OT, S, TE, Z> TracingStage<C, EM, I, OT, S, TE, Z>
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where
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C: Corpus<I>,
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M: Mutator<I, S>,
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I: Input,
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R: Rand,
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S: HasClientPerfStats + HasCorpus<C, I> + HasRand<R>,
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Z: Evaluator<E, EM, I, S>,
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C: Corpus<I>,
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TE: Executor<I>
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+ HasObservers<OT>
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+ HasExecHooks<EM, I, S, Z>
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+ HasObserversHooks<EM, I, OT, S, Z>,
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OT: ObserversTuple + HasExecHooksTuple<EM, I, S, Z>,
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S: HasClientPerfStats + HasExecutions + HasCorpus<C, I>,
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{
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/// Creates a new default mutational stage
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pub fn new(mutator: M) -> Self {
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pub fn new(tracer_executor: TE) -> Self {
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Self {
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mutator,
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tracer_executor,
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phantom: PhantomData,
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}
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}
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