forked from OSchip/llvm-project
				
			
		
			
				
	
	
		
			303 lines
		
	
	
		
			9.0 KiB
		
	
	
	
		
			C++
		
	
	
	
			
		
		
	
	
			303 lines
		
	
	
		
			9.0 KiB
		
	
	
	
		
			C++
		
	
	
	
//===- FuzzerCorpus.h - Internal header for the Fuzzer ----------*- C++ -* ===//
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//
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//                     The LLVM Compiler Infrastructure
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//
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// This file is distributed under the University of Illinois Open Source
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// License. See LICENSE.TXT for details.
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//
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//===----------------------------------------------------------------------===//
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// fuzzer::InputCorpus
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//===----------------------------------------------------------------------===//
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#ifndef LLVM_FUZZER_CORPUS
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#define LLVM_FUZZER_CORPUS
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#include "FuzzerDefs.h"
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#include "FuzzerIO.h"
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#include "FuzzerRandom.h"
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#include "FuzzerSHA1.h"
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#include "FuzzerTracePC.h"
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#include <algorithm>
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#include <numeric>
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#include <random>
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#include <unordered_set>
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namespace fuzzer {
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struct InputInfo {
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  Unit U;  // The actual input data.
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  uint8_t Sha1[kSHA1NumBytes];  // Checksum.
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  // Number of features that this input has and no smaller input has.
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  size_t NumFeatures = 0;
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  size_t Tmp = 0; // Used by ValidateFeatureSet.
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  // Stats.
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  size_t NumExecutedMutations = 0;
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  size_t NumSuccessfullMutations = 0;
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  bool MayDeleteFile = false;
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  bool Reduced = false;
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  Vector<uint32_t> UniqFeatureSet;
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  float FeatureFrequencyScore = 1.0;
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};
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class InputCorpus {
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  static const size_t kFeatureSetSize = 1 << 21;
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 public:
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  InputCorpus(const std::string &OutputCorpus) : OutputCorpus(OutputCorpus) {
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    memset(InputSizesPerFeature, 0, sizeof(InputSizesPerFeature));
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    memset(SmallestElementPerFeature, 0, sizeof(SmallestElementPerFeature));
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    memset(FeatureFrequency, 0, sizeof(FeatureFrequency));
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  }
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  ~InputCorpus() {
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    for (auto II : Inputs)
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      delete II;
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  }
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  size_t size() const { return Inputs.size(); }
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  size_t SizeInBytes() const {
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    size_t Res = 0;
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    for (auto II : Inputs)
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      Res += II->U.size();
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    return Res;
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  }
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  size_t NumActiveUnits() const {
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    size_t Res = 0;
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    for (auto II : Inputs)
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      Res += !II->U.empty();
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    return Res;
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  }
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  size_t MaxInputSize() const {
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    size_t Res = 0;
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    for (auto II : Inputs)
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        Res = std::max(Res, II->U.size());
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    return Res;
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  }
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  bool empty() const { return Inputs.empty(); }
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  const Unit &operator[] (size_t Idx) const { return Inputs[Idx]->U; }
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  void AddToCorpus(const Unit &U, size_t NumFeatures, bool MayDeleteFile,
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                   const Vector<uint32_t> &FeatureSet) {
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    assert(!U.empty());
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    if (FeatureDebug)
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      Printf("ADD_TO_CORPUS %zd NF %zd\n", Inputs.size(), NumFeatures);
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    Inputs.push_back(new InputInfo());
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    InputInfo &II = *Inputs.back();
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    II.U = U;
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    II.NumFeatures = NumFeatures;
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    II.MayDeleteFile = MayDeleteFile;
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    II.UniqFeatureSet = FeatureSet;
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    std::sort(II.UniqFeatureSet.begin(), II.UniqFeatureSet.end());
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    ComputeSHA1(U.data(), U.size(), II.Sha1);
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    Hashes.insert(Sha1ToString(II.Sha1));
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    UpdateCorpusDistribution();
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    PrintCorpus();
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    // ValidateFeatureSet();
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  }
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  // Debug-only
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  void PrintUnit(const Unit &U) {
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    if (!FeatureDebug) return;
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    for (uint8_t C : U) {
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      if (C != 'F' && C != 'U' && C != 'Z')
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        C = '.';
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      Printf("%c", C);
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    }
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  }
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  // Debug-only
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  void PrintFeatureSet(const Vector<uint32_t> &FeatureSet) {
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    if (!FeatureDebug) return;
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    Printf("{");
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    for (uint32_t Feature: FeatureSet)
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      Printf("%u,", Feature);
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    Printf("}");
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  }
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  // Debug-only
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  void PrintCorpus() {
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    if (!FeatureDebug) return;
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    Printf("======= CORPUS:\n");
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    int i = 0;
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    for (auto II : Inputs) {
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      if (std::find(II->U.begin(), II->U.end(), 'F') != II->U.end()) {
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        Printf("[%2d] ", i);
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        Printf("%s sz=%zd ", Sha1ToString(II->Sha1).c_str(), II->U.size());
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        PrintUnit(II->U);
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        Printf(" ");
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        PrintFeatureSet(II->UniqFeatureSet);
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        Printf("\n");
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      }
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      i++;
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    }
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  }
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  void Replace(InputInfo *II, const Unit &U) {
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    assert(II->U.size() > U.size());
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    Hashes.erase(Sha1ToString(II->Sha1));
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    DeleteFile(*II);
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    ComputeSHA1(U.data(), U.size(), II->Sha1);
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    Hashes.insert(Sha1ToString(II->Sha1));
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    II->U = U;
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    II->Reduced = true;
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    UpdateCorpusDistribution();
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  }
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  bool HasUnit(const Unit &U) { return Hashes.count(Hash(U)); }
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  bool HasUnit(const std::string &H) { return Hashes.count(H); }
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  InputInfo &ChooseUnitToMutate(Random &Rand) {
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    InputInfo &II = *Inputs[ChooseUnitIdxToMutate(Rand)];
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    assert(!II.U.empty());
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    return II;
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  };
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  // Returns an index of random unit from the corpus to mutate.
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  size_t ChooseUnitIdxToMutate(Random &Rand) {
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    size_t Idx = static_cast<size_t>(CorpusDistribution(Rand));
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    assert(Idx < Inputs.size());
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    return Idx;
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  }
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  void PrintStats() {
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    for (size_t i = 0; i < Inputs.size(); i++) {
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      const auto &II = *Inputs[i];
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      Printf("  [%zd %s]\tsz: %zd\truns: %zd\tsucc: %zd\n", i,
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             Sha1ToString(II.Sha1).c_str(), II.U.size(),
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             II.NumExecutedMutations, II.NumSuccessfullMutations);
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    }
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  }
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  void PrintFeatureSet() {
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    for (size_t i = 0; i < kFeatureSetSize; i++) {
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      if(size_t Sz = GetFeature(i))
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        Printf("[%zd: id %zd sz%zd] ", i, SmallestElementPerFeature[i], Sz);
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    }
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    Printf("\n\t");
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    for (size_t i = 0; i < Inputs.size(); i++)
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      if (size_t N = Inputs[i]->NumFeatures)
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        Printf(" %zd=>%zd ", i, N);
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    Printf("\n");
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  }
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  void DeleteFile(const InputInfo &II) {
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    if (!OutputCorpus.empty() && II.MayDeleteFile)
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      RemoveFile(DirPlusFile(OutputCorpus, Sha1ToString(II.Sha1)));
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  }
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  void DeleteInput(size_t Idx) {
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    InputInfo &II = *Inputs[Idx];
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    DeleteFile(II);
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    Unit().swap(II.U);
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    if (FeatureDebug)
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      Printf("EVICTED %zd\n", Idx);
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  }
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  bool AddFeature(size_t Idx, uint32_t NewSize, bool Shrink) {
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    assert(NewSize);
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    Idx = Idx % kFeatureSetSize;
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    uint32_t OldSize = GetFeature(Idx);
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    if (OldSize == 0 || (Shrink && OldSize > NewSize)) {
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      if (OldSize > 0) {
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        size_t OldIdx = SmallestElementPerFeature[Idx];
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        InputInfo &II = *Inputs[OldIdx];
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        assert(II.NumFeatures > 0);
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        II.NumFeatures--;
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        if (II.NumFeatures == 0)
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          DeleteInput(OldIdx);
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      } else {
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        NumAddedFeatures++;
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      }
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      NumUpdatedFeatures++;
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      if (FeatureDebug)
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        Printf("ADD FEATURE %zd sz %d\n", Idx, NewSize);
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      SmallestElementPerFeature[Idx] = Inputs.size();
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      InputSizesPerFeature[Idx] = NewSize;
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      return true;
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    }
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    return false;
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  }
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  void UpdateFeatureFrequency(size_t Idx) {
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    FeatureFrequency[Idx % kFeatureSetSize]++;
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  }
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  float GetFeatureFrequency(size_t Idx) const {
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    return FeatureFrequency[Idx % kFeatureSetSize];
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  }
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  void UpdateFeatureFrequencyScore(InputInfo *II) {
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    const float kMin = 0.01, kMax = 100.;
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    II->FeatureFrequencyScore = kMin;
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    for (auto Idx : II->UniqFeatureSet)
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      II->FeatureFrequencyScore += 1. / (GetFeatureFrequency(Idx) + 1.);
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    II->FeatureFrequencyScore = Min(II->FeatureFrequencyScore, kMax);
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  }
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  size_t NumFeatures() const { return NumAddedFeatures; }
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  size_t NumFeatureUpdates() const { return NumUpdatedFeatures; }
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private:
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  static const bool FeatureDebug = false;
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  size_t GetFeature(size_t Idx) const { return InputSizesPerFeature[Idx]; }
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  void ValidateFeatureSet() {
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    if (FeatureDebug)
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      PrintFeatureSet();
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    for (size_t Idx = 0; Idx < kFeatureSetSize; Idx++)
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      if (GetFeature(Idx))
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        Inputs[SmallestElementPerFeature[Idx]]->Tmp++;
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    for (auto II: Inputs) {
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      if (II->Tmp != II->NumFeatures)
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        Printf("ZZZ %zd %zd\n", II->Tmp, II->NumFeatures);
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      assert(II->Tmp == II->NumFeatures);
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      II->Tmp = 0;
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    }
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  }
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  // Updates the probability distribution for the units in the corpus.
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  // Must be called whenever the corpus or unit weights are changed.
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  //
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  // Hypothesis: units added to the corpus last are more interesting.
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  //
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  // Hypothesis: inputs with infrequent features are more interesting.
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  void UpdateCorpusDistribution() {
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    size_t N = Inputs.size();
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    assert(N);
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    Intervals.resize(N + 1);
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    Weights.resize(N);
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    std::iota(Intervals.begin(), Intervals.end(), 0);
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    for (size_t i = 0; i < N; i++)
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      Weights[i] = Inputs[i]->NumFeatures
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                       ? (i + 1) * Inputs[i]->FeatureFrequencyScore
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                       : 0.;
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    if (FeatureDebug) {
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      for (size_t i = 0; i < N; i++)
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        Printf("%zd ", Inputs[i]->NumFeatures);
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      Printf("NUM\n");
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      for (size_t i = 0; i < N; i++)
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        Printf("%f ", Inputs[i]->FeatureFrequencyScore);
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      Printf("SCORE\n");
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      for (size_t i = 0; i < N; i++)
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        Printf("%f ", Weights[i]);
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      Printf("Weights\n");
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    }
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    CorpusDistribution = std::piecewise_constant_distribution<double>(
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        Intervals.begin(), Intervals.end(), Weights.begin());
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  }
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  std::piecewise_constant_distribution<double> CorpusDistribution;
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  Vector<double> Intervals;
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  Vector<double> Weights;
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  std::unordered_set<std::string> Hashes;
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  Vector<InputInfo*> Inputs;
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  size_t NumAddedFeatures = 0;
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  size_t NumUpdatedFeatures = 0;
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  uint32_t InputSizesPerFeature[kFeatureSetSize];
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  uint32_t SmallestElementPerFeature[kFeatureSetSize];
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  float FeatureFrequency[kFeatureSetSize];
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  std::string OutputCorpus;
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};
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}  // namespace fuzzer
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#endif  // LLVM_FUZZER_CORPUS
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