The Tor Browser: ipc/chromium/src/base/histogram.cc@6474c204b198 (annotated)

ipc/chromium/src/base/histogram.cc@6474c204b198 (annotated)

ipc/chromium/src/base/histogram.cc

Wed, 31 Dec 2014 06:09:35 +0100

author: Michael Schloh von Bennewitz <michael@schloh.com>
date: Wed, 31 Dec 2014 06:09:35 +0100
changeset 0: 6474c204b198
permissions: -rw-r--r--

Cloned upstream origin tor-browser at tor-browser-31.3.0esr-4.5-1-build1
revision ID fc1c9ff7c1b2defdbc039f12214767608f46423f for hacking purpose.

 // Copyright (c) 2011 The Chromium Authors. All rights reserved.
 // Use of this source code is governed by a BSD-style license that can be
 // found in the LICENSE file.
 // Histogram is an object that aggregates statistics, and can summarize them in
 // various forms, including ASCII graphical, HTML, and numerically (as a
 // vector of numbers corresponding to each of the aggregating buckets).
 // See header file for details and examples.
 #include "base/histogram.h"
 #include <math.h>
 #include <algorithm>
 #include <string>
 #include "base/logging.h"
 #include "base/pickle.h"
 #include "base/string_util.h"
 #include "base/logging.h"
 namespace base {
 #define DVLOG(x) CHROMIUM_LOG(ERROR)
 #define CHECK_GT DCHECK_GT
 #define CHECK_LT DCHECK_LT
 typedef ::Lock Lock;
 typedef ::AutoLock AutoLock;
 // Static table of checksums for all possible 8 bit bytes.
 const uint32_t Histogram::kCrcTable[256] = {0x0, 0x77073096L, 0xee0e612cL,
 x990951baL, 0x76dc419L, 0x706af48fL, 0xe963a535L, 0x9e6495a3L, 0xedb8832L,
 x79dcb8a4L, 0xe0d5e91eL, 0x97d2d988L, 0x9b64c2bL, 0x7eb17cbdL, 0xe7b82d07L,
 x90bf1d91L, 0x1db71064L, 0x6ab020f2L, 0xf3b97148L, 0x84be41deL, 0x1adad47dL,
 x6ddde4ebL, 0xf4d4b551L, 0x83d385c7L, 0x136c9856L, 0x646ba8c0L, 0xfd62f97aL,
 x8a65c9ecL, 0x14015c4fL, 0x63066cd9L, 0xfa0f3d63L, 0x8d080df5L, 0x3b6e20c8L,
 x4c69105eL, 0xd56041e4L, 0xa2677172L, 0x3c03e4d1L, 0x4b04d447L, 0xd20d85fdL,
 xa50ab56bL, 0x35b5a8faL, 0x42b2986cL, 0xdbbbc9d6L, 0xacbcf940L, 0x32d86ce3L,
 x45df5c75L, 0xdcd60dcfL, 0xabd13d59L, 0x26d930acL, 0x51de003aL, 0xc8d75180L,
 xbfd06116L, 0x21b4f4b5L, 0x56b3c423L, 0xcfba9599L, 0xb8bda50fL, 0x2802b89eL,
 x5f058808L, 0xc60cd9b2L, 0xb10be924L, 0x2f6f7c87L, 0x58684c11L, 0xc1611dabL,
 xb6662d3dL, 0x76dc4190L, 0x1db7106L, 0x98d220bcL, 0xefd5102aL, 0x71b18589L,
 x6b6b51fL, 0x9fbfe4a5L, 0xe8b8d433L, 0x7807c9a2L, 0xf00f934L, 0x9609a88eL,
 xe10e9818L, 0x7f6a0dbbL, 0x86d3d2dL, 0x91646c97L, 0xe6635c01L, 0x6b6b51f4L,
 x1c6c6162L, 0x856530d8L, 0xf262004eL, 0x6c0695edL, 0x1b01a57bL, 0x8208f4c1L,
 xf50fc457L, 0x65b0d9c6L, 0x12b7e950L, 0x8bbeb8eaL, 0xfcb9887cL, 0x62dd1ddfL,
 x15da2d49L, 0x8cd37cf3L, 0xfbd44c65L, 0x4db26158L, 0x3ab551ceL, 0xa3bc0074L,
 xd4bb30e2L, 0x4adfa541L, 0x3dd895d7L, 0xa4d1c46dL, 0xd3d6f4fbL, 0x4369e96aL,
 x346ed9fcL, 0xad678846L, 0xda60b8d0L, 0x44042d73L, 0x33031de5L, 0xaa0a4c5fL,
 xdd0d7cc9L, 0x5005713cL, 0x270241aaL, 0xbe0b1010L, 0xc90c2086L, 0x5768b525L,
 x206f85b3L, 0xb966d409L, 0xce61e49fL, 0x5edef90eL, 0x29d9c998L, 0xb0d09822L,
 xc7d7a8b4L, 0x59b33d17L, 0x2eb40d81L, 0xb7bd5c3bL, 0xc0ba6cadL, 0xedb88320L,
 x9abfb3b6L, 0x3b6e20cL, 0x74b1d29aL, 0xead54739L, 0x9dd277afL, 0x4db2615L,
 x73dc1683L, 0xe3630b12L, 0x94643b84L, 0xd6d6a3eL, 0x7a6a5aa8L, 0xe40ecf0bL,
 x9309ff9dL, 0xa00ae27L, 0x7d079eb1L, 0xf00f9344L, 0x8708a3d2L, 0x1e01f268L,
 x6906c2feL, 0xf762575dL, 0x806567cbL, 0x196c3671L, 0x6e6b06e7L, 0xfed41b76L,
 x89d32be0L, 0x10da7a5aL, 0x67dd4accL, 0xf9b9df6fL, 0x8ebeeff9L, 0x17b7be43L,
 x60b08ed5L, 0xd6d6a3e8L, 0xa1d1937eL, 0x38d8c2c4L, 0x4fdff252L, 0xd1bb67f1L,
 xa6bc5767L, 0x3fb506ddL, 0x48b2364bL, 0xd80d2bdaL, 0xaf0a1b4cL, 0x36034af6L,
 x41047a60L, 0xdf60efc3L, 0xa867df55L, 0x316e8eefL, 0x4669be79L, 0xcb61b38cL,
 xbc66831aL, 0x256fd2a0L, 0x5268e236L, 0xcc0c7795L, 0xbb0b4703L, 0x220216b9L,
 x5505262fL, 0xc5ba3bbeL, 0xb2bd0b28L, 0x2bb45a92L, 0x5cb36a04L, 0xc2d7ffa7L,
 xb5d0cf31L, 0x2cd99e8bL, 0x5bdeae1dL, 0x9b64c2b0L, 0xec63f226L, 0x756aa39cL,
 x26d930aL, 0x9c0906a9L, 0xeb0e363fL, 0x72076785L, 0x5005713L, 0x95bf4a82L,
 xe2b87a14L, 0x7bb12baeL, 0xcb61b38L, 0x92d28e9bL, 0xe5d5be0dL, 0x7cdcefb7L,
 xbdbdf21L, 0x86d3d2d4L, 0xf1d4e242L, 0x68ddb3f8L, 0x1fda836eL, 0x81be16cdL,
 xf6b9265bL, 0x6fb077e1L, 0x18b74777L, 0x88085ae6L, 0xff0f6a70L, 0x66063bcaL,
 x11010b5cL, 0x8f659effL, 0xf862ae69L, 0x616bffd3L, 0x166ccf45L, 0xa00ae278L,
 xd70dd2eeL, 0x4e048354L, 0x3903b3c2L, 0xa7672661L, 0xd06016f7L, 0x4969474dL,
 x3e6e77dbL, 0xaed16a4aL, 0xd9d65adcL, 0x40df0b66L, 0x37d83bf0L, 0xa9bcae53L,
 xdebb9ec5L, 0x47b2cf7fL, 0x30b5ffe9L, 0xbdbdf21cL, 0xcabac28aL, 0x53b39330L,
 x24b4a3a6L, 0xbad03605L, 0xcdd70693L, 0x54de5729L, 0x23d967bfL, 0xb3667a2eL,
 xc4614ab8L, 0x5d681b02L, 0x2a6f2b94L, 0xb40bbe37L, 0xc30c8ea1L, 0x5a05df1bL,
 x2d02ef8dL,
 };
 typedef Histogram::Count Count;
 // static
 const size_t Histogram::kBucketCount_MAX = 16384u;
 Histogram* Histogram::FactoryGet(const std::string& name,
                                  Sample minimum,
                                  Sample maximum,
                                  size_t bucket_count,
                                  Flags flags) {
   Histogram* histogram(NULL);
   // Defensive code.
   if (minimum < 1)
     minimum = 1;
   if (maximum > kSampleType_MAX - 1)
     maximum = kSampleType_MAX - 1;
   if (!StatisticsRecorder::FindHistogram(name, &histogram)) {
     // Extra variable is not needed... but this keeps this section basically
     // identical to other derived classes in this file (and compiler will
     // optimize away the extra variable.
     Histogram* tentative_histogram =
         new Histogram(name, minimum, maximum, bucket_count);
     tentative_histogram->InitializeBucketRange();
     tentative_histogram->SetFlags(flags);
     histogram =
         StatisticsRecorder::RegisterOrDeleteDuplicate(tentative_histogram);
   }
   DCHECK_EQ(HISTOGRAM, histogram->histogram_type());
   DCHECK(histogram->HasConstructorArguments(minimum, maximum, bucket_count));
   return histogram;
 }
 Histogram* Histogram::FactoryTimeGet(const std::string& name,
                                      TimeDelta minimum,
                                      TimeDelta maximum,
                                      size_t bucket_count,
                                      Flags flags) {
   return FactoryGet(name, minimum.InMilliseconds(), maximum.InMilliseconds(),
                     bucket_count, flags);
 }
 void Histogram::Add(int value) {
   if (value > kSampleType_MAX - 1)
     value = kSampleType_MAX - 1;
   if (value < 0)
     value = 0;
   size_t index = BucketIndex(value);
   DCHECK_GE(value, ranges(index));
   DCHECK_LT(value, ranges(index + 1));
   Accumulate(value, 1, index);
 }
 void Histogram::Subtract(int value) {
   if (value > kSampleType_MAX - 1)
     value = kSampleType_MAX - 1;
   if (value < 0)
     value = 0;
   size_t index = BucketIndex(value);
   DCHECK_GE(value, ranges(index));
   DCHECK_LT(value, ranges(index + 1));
   Accumulate(value, -1, index);
 }
 void Histogram::AddBoolean(bool value) {
   DCHECK(false);
 }
 void Histogram::AddSampleSet(const SampleSet& sample) {
   sample_.Add(sample);
 }
 void Histogram::Clear() {
   SampleSet ss;
   ss.Resize(*this);
   sample_ = ss;
 }
 void Histogram::SetRangeDescriptions(const DescriptionPair descriptions[]) {
   DCHECK(false);
 }
 // The following methods provide a graphical histogram display.
 void Histogram::WriteHTMLGraph(std::string* output) const {
   // TBD(jar) Write a nice HTML bar chart, with divs an mouse-overs etc.
   output->append("<PRE>");
   WriteAscii(true, "<br>", output);
   output->append("</PRE>");
 }
 void Histogram::WriteAscii(bool graph_it, const std::string& newline,
                            std::string* output) const {
   // Get local (stack) copies of all effectively volatile class data so that we
   // are consistent across our output activities.
   SampleSet snapshot;
   SnapshotSample(&snapshot);
   Count sample_count = snapshot.TotalCount();
   WriteAsciiHeader(snapshot, sample_count, output);
   output->append(newline);
   // Prepare to normalize graphical rendering of bucket contents.
   double max_size = 0;
   if (graph_it)
     max_size = GetPeakBucketSize(snapshot);
   // Calculate space needed to print bucket range numbers.  Leave room to print
   // nearly the largest bucket range without sliding over the histogram.
   size_t largest_non_empty_bucket = bucket_count() - 1;
   while (0 == snapshot.counts(largest_non_empty_bucket)) {
     if (0 == largest_non_empty_bucket)
       break;  // All buckets are empty.
     --largest_non_empty_bucket;
   }
   // Calculate largest print width needed for any of our bucket range displays.
   size_t print_width = 1;
   for (size_t i = 0; i < bucket_count(); ++i) {
     if (snapshot.counts(i)) {
       size_t width = GetAsciiBucketRange(i).size() + 1;
       if (width > print_width)
         print_width = width;
     }
   }
   int64_t remaining = sample_count;
   int64_t past = 0;
   // Output the actual histogram graph.
   for (size_t i = 0; i < bucket_count(); ++i) {
     Count current = snapshot.counts(i);
     if (!current && !PrintEmptyBucket(i))
       continue;
     remaining -= current;
     std::string range = GetAsciiBucketRange(i);
     output->append(range);
     for (size_t j = 0; range.size() + j < print_width + 1; ++j)
       output->push_back(' ');
     if (0 == current && i < bucket_count() - 1 && 0 == snapshot.counts(i + 1)) {
       while (i < bucket_count() - 1 && 0 == snapshot.counts(i + 1))
         ++i;
       output->append("... ");
       output->append(newline);
       continue;  // No reason to plot emptiness.
     }
     double current_size = GetBucketSize(current, i);
     if (graph_it)
       WriteAsciiBucketGraph(current_size, max_size, output);
     WriteAsciiBucketContext(past, current, remaining, i, output);
     output->append(newline);
     past += current;
   }
   DCHECK_EQ(sample_count, past);
 }
 // static
 std::string Histogram::SerializeHistogramInfo(const Histogram& histogram,
                                               const SampleSet& snapshot) {
   DCHECK_NE(NOT_VALID_IN_RENDERER, histogram.histogram_type());
   Pickle pickle;
   pickle.WriteString(histogram.histogram_name());
   pickle.WriteInt(histogram.declared_min());
   pickle.WriteInt(histogram.declared_max());
   pickle.WriteSize(histogram.bucket_count());
   pickle.WriteUInt32(histogram.range_checksum());
   pickle.WriteInt(histogram.histogram_type());
   pickle.WriteInt(histogram.flags());
   snapshot.Serialize(&pickle);
   return std::string(static_cast<const char*>(pickle.data()), pickle.size());
 }
 // static
 bool Histogram::DeserializeHistogramInfo(const std::string& histogram_info) {
   if (histogram_info.empty()) {
       return false;
   }
   Pickle pickle(histogram_info.data(),
                 static_cast<int>(histogram_info.size()));
   std::string histogram_name;
   int declared_min;
   int declared_max;
   size_t bucket_count;
   uint32_t range_checksum;
   int histogram_type;
   int pickle_flags;
   SampleSet sample;
   void* iter = NULL;
   if (!pickle.ReadString(&iter, &histogram_name) ||
       !pickle.ReadInt(&iter, &declared_min) ||
       !pickle.ReadInt(&iter, &declared_max) ||
       !pickle.ReadSize(&iter, &bucket_count) ||
       !pickle.ReadUInt32(&iter, &range_checksum) ||
       !pickle.ReadInt(&iter, &histogram_type) ||
       !pickle.ReadInt(&iter, &pickle_flags) ||
       !sample.Histogram::SampleSet::Deserialize(&iter, pickle)) {
     CHROMIUM_LOG(ERROR) << "Pickle error decoding Histogram: " << histogram_name;
     return false;
   }
   DCHECK(pickle_flags & kIPCSerializationSourceFlag);
   // Since these fields may have come from an untrusted renderer, do additional
   // checks above and beyond those in Histogram::Initialize()
   if (declared_max <= 0 || declared_min <= 0 || declared_max < declared_min ||
       INT_MAX / sizeof(Count) <= bucket_count || bucket_count < 2) {
     CHROMIUM_LOG(ERROR) << "Values error decoding Histogram: " << histogram_name;
     return false;
   }
   Flags flags = static_cast<Flags>(pickle_flags & ~kIPCSerializationSourceFlag);
   DCHECK_NE(NOT_VALID_IN_RENDERER, histogram_type);
   Histogram* render_histogram(NULL);
   if (histogram_type == HISTOGRAM) {
     render_histogram = Histogram::FactoryGet(
         histogram_name, declared_min, declared_max, bucket_count, flags);
   } else if (histogram_type == LINEAR_HISTOGRAM) {
     render_histogram = LinearHistogram::FactoryGet(
         histogram_name, declared_min, declared_max, bucket_count, flags);
   } else if (histogram_type == BOOLEAN_HISTOGRAM) {
     render_histogram = BooleanHistogram::FactoryGet(histogram_name, flags);
   } else {
     CHROMIUM_LOG(ERROR) << "Error Deserializing Histogram Unknown histogram_type: "
                         << histogram_type;
     return false;
   }
   DCHECK_EQ(render_histogram->declared_min(), declared_min);
   DCHECK_EQ(render_histogram->declared_max(), declared_max);
   DCHECK_EQ(render_histogram->bucket_count(), bucket_count);
   DCHECK_EQ(render_histogram->range_checksum(), range_checksum);
   DCHECK_EQ(render_histogram->histogram_type(), histogram_type);
   if (render_histogram->flags() & kIPCSerializationSourceFlag) {
     DVLOG(1) << "Single process mode, histogram observed and not copied: "
              << histogram_name;
   } else {
     DCHECK_EQ(flags & render_histogram->flags(), flags);
     render_histogram->AddSampleSet(sample);
   }
   return true;
 }
 //------------------------------------------------------------------------------
 // Methods for the validating a sample and a related histogram.
 //------------------------------------------------------------------------------
 Histogram::Inconsistencies Histogram::FindCorruption(
     const SampleSet& snapshot) const {
   int inconsistencies = NO_INCONSISTENCIES;
   Sample previous_range = -1;  // Bottom range is always 0.
   int64_t count = 0;
   for (size_t index = 0; index < bucket_count(); ++index) {
     count += snapshot.counts(index);
     int new_range = ranges(index);
     if (previous_range >= new_range)
       inconsistencies |= BUCKET_ORDER_ERROR;
     previous_range = new_range;
   }
   if (!HasValidRangeChecksum())
     inconsistencies |= RANGE_CHECKSUM_ERROR;
   int64_t delta64 = snapshot.redundant_count() - count;
   if (delta64 != 0) {
     int delta = static_cast<int>(delta64);
     if (delta != delta64)
       delta = INT_MAX;  // Flag all giant errors as INT_MAX.
     // Since snapshots of histograms are taken asynchronously relative to
     // sampling (and snapped from different threads), it is pretty likely that
     // we'll catch a redundant count that doesn't match the sample count.  We
     // allow for a certain amount of slop before flagging this as an
     // inconsistency.  Even with an inconsistency, we'll snapshot it again (for
     // UMA in about a half hour, so we'll eventually get the data, if it was
     // not the result of a corruption.  If histograms show that 1 is "too tight"
     // then we may try to use 2 or 3 for this slop value.
     const int kCommonRaceBasedCountMismatch = 1;
     if (delta > 0) {
       UMA_HISTOGRAM_COUNTS("Histogram.InconsistentCountHigh", delta);
       if (delta > kCommonRaceBasedCountMismatch)
         inconsistencies |= COUNT_HIGH_ERROR;
     } else {
       DCHECK_GT(0, delta);
       UMA_HISTOGRAM_COUNTS("Histogram.InconsistentCountLow", -delta);
       if (-delta > kCommonRaceBasedCountMismatch)
         inconsistencies |= COUNT_LOW_ERROR;
     }
   }
   return static_cast<Inconsistencies>(inconsistencies);
 }
 Histogram::ClassType Histogram::histogram_type() const {
   return HISTOGRAM;
 }
 Histogram::Sample Histogram::ranges(size_t i) const {
   return ranges_[i];
 }
 size_t Histogram::bucket_count() const {
   return bucket_count_;
 }
 // Do a safe atomic snapshot of sample data.
 // This implementation assumes we are on a safe single thread.
 void Histogram::SnapshotSample(SampleSet* sample) const {
   // Note locking not done in this version!!!
   *sample = sample_;
 }
 bool Histogram::HasConstructorArguments(Sample minimum,
                                         Sample maximum,
                                         size_t bucket_count) {
   return ((minimum == declared_min_) && (maximum == declared_max_) &&
           (bucket_count == bucket_count_));
 }
 bool Histogram::HasConstructorTimeDeltaArguments(TimeDelta minimum,
                                                  TimeDelta maximum,
                                                  size_t bucket_count) {
   return ((minimum.InMilliseconds() == declared_min_) &&
           (maximum.InMilliseconds() == declared_max_) &&
           (bucket_count == bucket_count_));
 }
 bool Histogram::HasValidRangeChecksum() const {
   return CalculateRangeChecksum() == range_checksum_;
 }
 size_t Histogram::SizeOfIncludingThis(mozilla::MallocSizeOf aMallocSizeOf)
 {
   size_t n = 0;
   n += aMallocSizeOf(this);
   // We're not allowed to do deep dives into STL data structures.  This
   // is as close as we can get to measuring this array.
   n += aMallocSizeOf(&ranges_[0]);
   n += sample_.SizeOfExcludingThis(aMallocSizeOf);
   return n;
 }
 size_t Histogram::SampleSet::SizeOfExcludingThis(mozilla::MallocSizeOf aMallocSizeOf)
 {
   // We're not allowed to do deep dives into STL data structures.  This
   // is as close as we can get to measuring this array.
   return aMallocSizeOf(&counts_[0]);
 }
 Histogram::Histogram(const std::string& name, Sample minimum,
                      Sample maximum, size_t bucket_count)
   : sample_(),
     histogram_name_(name),
     declared_min_(minimum),
     declared_max_(maximum),
     bucket_count_(bucket_count),
     flags_(kNoFlags),
     ranges_(bucket_count + 1, 0),
     range_checksum_(0) {
   Initialize();
 }
 Histogram::Histogram(const std::string& name, TimeDelta minimum,
                      TimeDelta maximum, size_t bucket_count)
   : sample_(),
     histogram_name_(name),
     declared_min_(static_cast<int> (minimum.InMilliseconds())),
     declared_max_(static_cast<int> (maximum.InMilliseconds())),
     bucket_count_(bucket_count),
     flags_(kNoFlags),
     ranges_(bucket_count + 1, 0),
     range_checksum_(0) {
   Initialize();
 }
 Histogram::~Histogram() {
   if (StatisticsRecorder::dump_on_exit()) {
     std::string output;
     WriteAscii(true, "\n", &output);
     CHROMIUM_LOG(INFO) << output;
   }
   // Just to make sure most derived class did this properly...
   DCHECK(ValidateBucketRanges());
 }
 // Calculate what range of values are held in each bucket.
 // We have to be careful that we don't pick a ratio between starting points in
 // consecutive buckets that is sooo small, that the integer bounds are the same
 // (effectively making one bucket get no values).  We need to avoid:
 //   ranges_[i] == ranges_[i + 1]
 // To avoid that, we just do a fine-grained bucket width as far as we need to
 // until we get a ratio that moves us along at least 2 units at a time.  From
 // that bucket onward we do use the exponential growth of buckets.
 void Histogram::InitializeBucketRange() {
   double log_max = log(static_cast<double>(declared_max()));
   double log_ratio;
   double log_next;
   size_t bucket_index = 1;
   Sample current = declared_min();
   SetBucketRange(bucket_index, current);
   while (bucket_count() > ++bucket_index) {
     double log_current;
     log_current = log(static_cast<double>(current));
     // Calculate the count'th root of the range.
     log_ratio = (log_max - log_current) / (bucket_count() - bucket_index);
     // See where the next bucket would start.
     log_next = log_current + log_ratio;
     int next;
     next = static_cast<int>(floor(exp(log_next) + 0.5));
     if (next > current)
       current = next;
     else
       ++current;  // Just do a narrow bucket, and keep trying.
     SetBucketRange(bucket_index, current);
   }
   ResetRangeChecksum();
   DCHECK_EQ(bucket_count(), bucket_index);
 }
 bool Histogram::PrintEmptyBucket(size_t index) const {
   return true;
 }
 size_t Histogram::BucketIndex(Sample value) const {
   // Use simple binary search.  This is very general, but there are better
   // approaches if we knew that the buckets were linearly distributed.
   DCHECK_LE(ranges(0), value);
   DCHECK_GT(ranges(bucket_count()), value);
   size_t under = 0;
   size_t over = bucket_count();
   size_t mid;
   do {
     DCHECK_GE(over, under);
     mid = under + (over - under)/2;
     if (mid == under)
       break;
     if (ranges(mid) <= value)
       under = mid;
     else
       over = mid;
   } while (true);
   DCHECK_LE(ranges(mid), value);
   CHECK_GT(ranges(mid+1), value);
   return mid;
 }
 // Use the actual bucket widths (like a linear histogram) until the widths get
 // over some transition value, and then use that transition width.  Exponentials
 // get so big so fast (and we don't expect to see a lot of entries in the large
 // buckets), so we need this to make it possible to see what is going on and
 // not have 0-graphical-height buckets.
 double Histogram::GetBucketSize(Count current, size_t i) const {
   DCHECK_GT(ranges(i + 1), ranges(i));
   static const double kTransitionWidth = 5;
   double denominator = ranges(i + 1) - ranges(i);
   if (denominator > kTransitionWidth)
     denominator = kTransitionWidth;  // Stop trying to normalize.
   return current/denominator;
 }
 void Histogram::ResetRangeChecksum() {
   range_checksum_ = CalculateRangeChecksum();
 }
 const std::string Histogram::GetAsciiBucketRange(size_t i) const {
   std::string result;
   if (kHexRangePrintingFlag & flags_)
     StringAppendF(&result, "%#x", ranges(i));
   else
     StringAppendF(&result, "%d", ranges(i));
   return result;
 }
 // Update histogram data with new sample.
 void Histogram::Accumulate(Sample value, Count count, size_t index) {
   // Note locking not done in this version!!!
   sample_.AccumulateWithExponentialStats(value, count, index,
 					 flags_ & kExtendedStatisticsFlag);
 }
 void Histogram::SetBucketRange(size_t i, Sample value) {
   DCHECK_GT(bucket_count_, i);
   ranges_[i] = value;
 }
 bool Histogram::ValidateBucketRanges() const {
   // Standard assertions that all bucket ranges should satisfy.
   DCHECK_EQ(bucket_count_ + 1, ranges_.size());
   DCHECK_EQ(0, ranges_[0]);
   DCHECK_EQ(declared_min(), ranges_[1]);
   DCHECK_EQ(declared_max(), ranges_[bucket_count_ - 1]);
   DCHECK_EQ(kSampleType_MAX, ranges_[bucket_count_]);
   return true;
 }
 uint32_t Histogram::CalculateRangeChecksum() const {
   DCHECK_EQ(ranges_.size(), bucket_count() + 1);
   uint32_t checksum = static_cast<uint32_t>(ranges_.size());  // Seed checksum.
   for (size_t index = 0; index < bucket_count(); ++index)
     checksum = Crc32(checksum, ranges(index));
   return checksum;
 }
 void Histogram::Initialize() {
   sample_.Resize(*this);
   if (declared_min_ < 1)
     declared_min_ = 1;
   if (declared_max_ > kSampleType_MAX - 1)
     declared_max_ = kSampleType_MAX - 1;
   DCHECK_LE(declared_min_, declared_max_);
   DCHECK_GT(bucket_count_, 1u);
   CHECK_LT(bucket_count_, kBucketCount_MAX);
   size_t maximal_bucket_count = declared_max_ - declared_min_ + 2;
   DCHECK_LE(bucket_count_, maximal_bucket_count);
   DCHECK_EQ(0, ranges_[0]);
   ranges_[bucket_count_] = kSampleType_MAX;
 }
 // We generate the CRC-32 using the low order bits to select whether to XOR in
 // the reversed polynomial 0xedb88320L.  This is nice and simple, and allows us
 // to keep the quotient in a uint32_t.  Since we're not concerned about the nature
 // of corruptions (i.e., we don't care about bit sequencing, since we are
 // handling memory changes, which are more grotesque) so we don't bother to
 // get the CRC correct for big-endian vs little-ending calculations.  All we
 // need is a nice hash, that tends to depend on all the bits of the sample, with
 // very little chance of changes in one place impacting changes in another
 // place.
 uint32_t Histogram::Crc32(uint32_t sum, Histogram::Sample range) {
   const bool kUseRealCrc = true;  // TODO(jar): Switch to false and watch stats.
   if (kUseRealCrc) {
     union {
       Histogram::Sample range;
       unsigned char bytes[sizeof(Histogram::Sample)];
     } converter;
     converter.range = range;
     for (size_t i = 0; i < sizeof(converter); ++i)
       sum = kCrcTable[(sum & 0xff) ^ converter.bytes[i]] ^ (sum >> 8);
   } else {
     // Use hash techniques provided in ReallyFastHash, except we don't care
     // about "avalanching" (which would worsten the hash, and add collisions),
     // and we don't care about edge cases since we have an even number of bytes.
     union {
       Histogram::Sample range;
       uint16_t ints[sizeof(Histogram::Sample) / 2];
     } converter;
     DCHECK_EQ(sizeof(Histogram::Sample), sizeof(converter));
     converter.range = range;
     sum += converter.ints[0];
     sum = (sum << 16) ^ sum ^ (static_cast<uint32_t>(converter.ints[1]) << 11);
     sum += sum >> 11;
   }
   return sum;
 }
 //------------------------------------------------------------------------------
 // Private methods
 double Histogram::GetPeakBucketSize(const SampleSet& snapshot) const {
   double max = 0;
   for (size_t i = 0; i < bucket_count() ; ++i) {
     double current_size = GetBucketSize(snapshot.counts(i), i);
     if (current_size > max)
       max = current_size;
   }
   return max;
 }
 void Histogram::WriteAsciiHeader(const SampleSet& snapshot,
                                  Count sample_count,
                                  std::string* output) const {
   StringAppendF(output,
                 "Histogram: %s recorded %d samples",
                 histogram_name().c_str(),
                 sample_count);
   if (0 == sample_count) {
     DCHECK_EQ(snapshot.sum(), 0);
   } else {
     double average = static_cast<float>(snapshot.sum()) / sample_count;
     StringAppendF(output, ", average = %.1f", average);
   }
   if (flags_ & ~kHexRangePrintingFlag)
     StringAppendF(output, " (flags = 0x%x)", flags_ & ~kHexRangePrintingFlag);
 }
 void Histogram::WriteAsciiBucketContext(const int64_t past,
                                         const Count current,
                                         const int64_t remaining,
                                         const size_t i,
                                         std::string* output) const {
   double scaled_sum = (past + current + remaining) / 100.0;
   WriteAsciiBucketValue(current, scaled_sum, output);
   if (0 < i) {
     double percentage = past / scaled_sum;
     StringAppendF(output, " {%3.1f%%}", percentage);
   }
 }
 void Histogram::WriteAsciiBucketValue(Count current, double scaled_sum,
                                       std::string* output) const {
   StringAppendF(output, " (%d = %3.1f%%)", current, current/scaled_sum);
 }
 void Histogram::WriteAsciiBucketGraph(double current_size, double max_size,
                                       std::string* output) const {
   const int k_line_length = 72;  // Maximal horizontal width of graph.
   int x_count = static_cast<int>(k_line_length * (current_size / max_size)
                                  + 0.5);
   int x_remainder = k_line_length - x_count;
   while (0 < x_count--)
     output->append("-");
   output->append("O");
   while (0 < x_remainder--)
     output->append(" ");
 }
 //------------------------------------------------------------------------------
 // Methods for the Histogram::SampleSet class
 //------------------------------------------------------------------------------
 Histogram::SampleSet::SampleSet()
     : counts_(),
       sum_(0),
       sum_squares_(0),
       log_sum_(0),
       log_sum_squares_(0),
       redundant_count_(0) {
 }
 Histogram::SampleSet::~SampleSet() {
 }
 void Histogram::SampleSet::Resize(const Histogram& histogram) {
   counts_.resize(histogram.bucket_count(), 0);
 }
 void Histogram::SampleSet::CheckSize(const Histogram& histogram) const {
   DCHECK_EQ(histogram.bucket_count(), counts_.size());
 }
 void Histogram::SampleSet::Accumulate(Sample value, Count count,
 				      size_t index) {
   DCHECK(count == 1 || count == -1);
   counts_[index] += count;
   redundant_count_ += count;
   sum_ += static_cast<int64_t>(count) * value;
   DCHECK_GE(counts_[index], 0);
   DCHECK_GE(sum_, 0);
   DCHECK_GE(redundant_count_, 0);
 }
 void Histogram::SampleSet::AccumulateWithLinearStats(Sample value,
                                                      Count count,
                                                      size_t index) {
   Accumulate(value, count, index);
   sum_squares_ += static_cast<int64_t>(count) * value * value;
 }
 void Histogram::SampleSet::AccumulateWithExponentialStats(Sample value,
                                                           Count count,
                                                           size_t index,
 							  bool computeExtendedStatistics) {
   Accumulate(value, count, index);
   if (computeExtendedStatistics) {
     DCHECK_GE(value, 0);
     float value_log = logf(static_cast<float>(value) + 1.0f);
     log_sum_ += count * value_log;
     log_sum_squares_ += count * value_log * value_log;
   }
 }
 Count Histogram::SampleSet::TotalCount() const {
   Count total = 0;
   for (Counts::const_iterator it = counts_.begin();
        it != counts_.end();
        ++it) {
     total += *it;
   }
   return total;
 }
 void Histogram::SampleSet::Add(const SampleSet& other) {
   DCHECK_EQ(counts_.size(), other.counts_.size());
   sum_ += other.sum_;
   sum_squares_ += other.sum_squares_;
   log_sum_ += other.log_sum_;
   log_sum_squares_ += other.log_sum_squares_;
   redundant_count_ += other.redundant_count_;
   for (size_t index = 0; index < counts_.size(); ++index)
     counts_[index] += other.counts_[index];
 }
 void Histogram::SampleSet::Subtract(const SampleSet& other) {
   DCHECK_EQ(counts_.size(), other.counts_.size());
   // Note: Race conditions in snapshotting a sum may lead to (temporary)
   // negative values when snapshots are later combined (and deltas calculated).
   // As a result, we don't currently CHCEK() for positive values.
   sum_ -= other.sum_;
   sum_squares_ -= other.sum_squares_;
   log_sum_ -= other.log_sum_;
   log_sum_squares_ -= other.log_sum_squares_;
   redundant_count_ -= other.redundant_count_;
   for (size_t index = 0; index < counts_.size(); ++index) {
     counts_[index] -= other.counts_[index];
     DCHECK_GE(counts_[index], 0);
   }
 }
 bool Histogram::SampleSet::Serialize(Pickle* pickle) const {
   pickle->WriteInt64(sum_);
   pickle->WriteInt64(redundant_count_);
   pickle->WriteSize(counts_.size());
   for (size_t index = 0; index < counts_.size(); ++index) {
     pickle->WriteInt(counts_[index]);
   }
   return true;
 }
 bool Histogram::SampleSet::Deserialize(void** iter, const Pickle& pickle) {
   DCHECK_EQ(counts_.size(), 0u);
   DCHECK_EQ(sum_, 0);
   DCHECK_EQ(redundant_count_, 0);
   size_t counts_size;
   if (!pickle.ReadInt64(iter, &sum_) ||
       !pickle.ReadInt64(iter, &redundant_count_) ||
       !pickle.ReadSize(iter, &counts_size)) {
     return false;
   }
   if (counts_size == 0)
     return false;
   int count = 0;
   for (size_t index = 0; index < counts_size; ++index) {
     int i;
     if (!pickle.ReadInt(iter, &i))
       return false;
     counts_.push_back(i);
     count += i;
   }
   return true;
 }
 //------------------------------------------------------------------------------
 // LinearHistogram: This histogram uses a traditional set of evenly spaced
 // buckets.
 //------------------------------------------------------------------------------
 LinearHistogram::~LinearHistogram() {
 }
 Histogram* LinearHistogram::FactoryGet(const std::string& name,
                                        Sample minimum,
                                        Sample maximum,
                                        size_t bucket_count,
                                        Flags flags) {
   Histogram* histogram(NULL);
   if (minimum < 1)
     minimum = 1;
   if (maximum > kSampleType_MAX - 1)
     maximum = kSampleType_MAX - 1;
   if (!StatisticsRecorder::FindHistogram(name, &histogram)) {
     LinearHistogram* tentative_histogram =
         new LinearHistogram(name, minimum, maximum, bucket_count);
     tentative_histogram->InitializeBucketRange();
     tentative_histogram->SetFlags(flags);
     histogram =
         StatisticsRecorder::RegisterOrDeleteDuplicate(tentative_histogram);
   }
   DCHECK_EQ(LINEAR_HISTOGRAM, histogram->histogram_type());
   DCHECK(histogram->HasConstructorArguments(minimum, maximum, bucket_count));
   return histogram;
 }
 Histogram* LinearHistogram::FactoryTimeGet(const std::string& name,
                                            TimeDelta minimum,
                                            TimeDelta maximum,
                                            size_t bucket_count,
                                            Flags flags) {
   return FactoryGet(name, minimum.InMilliseconds(), maximum.InMilliseconds(),
                     bucket_count, flags);
 }
 Histogram::ClassType LinearHistogram::histogram_type() const {
   return LINEAR_HISTOGRAM;
 }
 void LinearHistogram::Accumulate(Sample value, Count count, size_t index) {
   sample_.AccumulateWithLinearStats(value, count, index);
 }
 void LinearHistogram::SetRangeDescriptions(
     const DescriptionPair descriptions[]) {
   for (int i =0; descriptions[i].description; ++i) {
     bucket_description_[descriptions[i].sample] = descriptions[i].description;
   }
 }
 LinearHistogram::LinearHistogram(const std::string& name,
                                  Sample minimum,
                                  Sample maximum,
                                  size_t bucket_count)
     : Histogram(name, minimum >= 1 ? minimum : 1, maximum, bucket_count) {
 }
 LinearHistogram::LinearHistogram(const std::string& name,
                                  TimeDelta minimum,
                                  TimeDelta maximum,
                                  size_t bucket_count)
     : Histogram(name, minimum >= TimeDelta::FromMilliseconds(1) ?
                                  minimum : TimeDelta::FromMilliseconds(1),
                 maximum, bucket_count) {
 }
 void LinearHistogram::InitializeBucketRange() {
   DCHECK_GT(declared_min(), 0);  // 0 is the underflow bucket here.
   double min = declared_min();
   double max = declared_max();
   size_t i;
   for (i = 1; i < bucket_count(); ++i) {
     double linear_range = (min * (bucket_count() -1 - i) + max * (i - 1)) /
                           (bucket_count() - 2);
     SetBucketRange(i, static_cast<int> (linear_range + 0.5));
   }
   ResetRangeChecksum();
 }
 double LinearHistogram::GetBucketSize(Count current, size_t i) const {
   DCHECK_GT(ranges(i + 1), ranges(i));
   // Adjacent buckets with different widths would have "surprisingly" many (few)
   // samples in a histogram if we didn't normalize this way.
   double denominator = ranges(i + 1) - ranges(i);
   return current/denominator;
 }
 const std::string LinearHistogram::GetAsciiBucketRange(size_t i) const {
   int range = ranges(i);
   BucketDescriptionMap::const_iterator it = bucket_description_.find(range);
   if (it == bucket_description_.end())
     return Histogram::GetAsciiBucketRange(i);
   return it->second;
 }
 bool LinearHistogram::PrintEmptyBucket(size_t index) const {
   return bucket_description_.find(ranges(index)) == bucket_description_.end();
 }
 //------------------------------------------------------------------------------
 // This section provides implementation for BooleanHistogram.
 //------------------------------------------------------------------------------
 Histogram* BooleanHistogram::FactoryGet(const std::string& name, Flags flags) {
   Histogram* histogram(NULL);
   if (!StatisticsRecorder::FindHistogram(name, &histogram)) {
     BooleanHistogram* tentative_histogram = new BooleanHistogram(name);
     tentative_histogram->InitializeBucketRange();
     tentative_histogram->SetFlags(flags);
     histogram =
         StatisticsRecorder::RegisterOrDeleteDuplicate(tentative_histogram);
   }
   DCHECK_EQ(BOOLEAN_HISTOGRAM, histogram->histogram_type());
   return histogram;
 }
 Histogram::ClassType BooleanHistogram::histogram_type() const {
   return BOOLEAN_HISTOGRAM;
 }
 void BooleanHistogram::AddBoolean(bool value) {
   Add(value ? 1 : 0);
 }
 BooleanHistogram::BooleanHistogram(const std::string& name)
     : LinearHistogram(name, 1, 2, 3) {
 }
 void
 BooleanHistogram::Accumulate(Sample value, Count count, size_t index)
 {
   // Callers will have computed index based on the non-booleanified value.
   // So we need to adjust the index manually.
   LinearHistogram::Accumulate(!!value, count, value ? 1 : 0);
 }
 //------------------------------------------------------------------------------
 // FlagHistogram:
 //------------------------------------------------------------------------------
 Histogram *
 FlagHistogram::FactoryGet(const std::string &name, Flags flags)
 {
   Histogram *h(nullptr);
   if (!StatisticsRecorder::FindHistogram(name, &h)) {
     FlagHistogram *fh = new FlagHistogram(name);
     fh->InitializeBucketRange();
     fh->SetFlags(flags);
     size_t zero_index = fh->BucketIndex(0);
     fh->LinearHistogram::Accumulate(0, 1, zero_index);
     h = StatisticsRecorder::RegisterOrDeleteDuplicate(fh);
   }
   return h;
 }
 FlagHistogram::FlagHistogram(const std::string &name)
   : BooleanHistogram(name), mSwitched(false) {
 }
 Histogram::ClassType
 FlagHistogram::histogram_type() const
 {
   return FLAG_HISTOGRAM;
 }
 void
 FlagHistogram::Accumulate(Sample value, Count count, size_t index)
 {
   if (mSwitched) {
     return;
   }
   mSwitched = true;
   DCHECK_EQ(value, 1);
   LinearHistogram::Accumulate(value, 1, index);
   size_t zero_index = BucketIndex(0);
   LinearHistogram::Accumulate(0, -1, zero_index);
 }
 void
 FlagHistogram::AddSampleSet(const SampleSet& sample) {
   DCHECK_EQ(bucket_count(), sample.size());
   // We can't be sure the SampleSet provided came from another FlagHistogram,
   // so we take the following steps:
   //  - If our flag has already been set do nothing.
   //  - Set our flag if the following hold:
   //      - The sum of the counts in the provided SampleSet is 1.
   //      - The bucket index for that single value is the same as the index where we
   //        would place our set flag.
   //  - Otherwise, take no action.
   if (mSwitched) {
     return;
   }
   if (sample.sum() != 1) {
     return;
   }
   size_t one_index = BucketIndex(1);
   if (sample.counts(one_index) == 1) {
     Accumulate(1, 1, one_index);
   }
 }
 //------------------------------------------------------------------------------
 // CustomHistogram:
 //------------------------------------------------------------------------------
 Histogram* CustomHistogram::FactoryGet(const std::string& name,
                                        const std::vector<Sample>& custom_ranges,
                                        Flags flags) {
   Histogram* histogram(NULL);
   // Remove the duplicates in the custom ranges array.
   std::vector<int> ranges = custom_ranges;
   ranges.push_back(0);  // Ensure we have a zero value.
   std::sort(ranges.begin(), ranges.end());
   ranges.erase(std::unique(ranges.begin(), ranges.end()), ranges.end());
   if (ranges.size() <= 1) {
     DCHECK(false);
     // Note that we pushed a 0 in above, so for defensive code....
     ranges.push_back(1);  // Put in some data so we can index to [1].
   }
   DCHECK_LT(ranges.back(), kSampleType_MAX);
   if (!StatisticsRecorder::FindHistogram(name, &histogram)) {
     CustomHistogram* tentative_histogram = new CustomHistogram(name, ranges);
     tentative_histogram->InitializedCustomBucketRange(ranges);
     tentative_histogram->SetFlags(flags);
     histogram =
         StatisticsRecorder::RegisterOrDeleteDuplicate(tentative_histogram);
   }
   DCHECK_EQ(histogram->histogram_type(), CUSTOM_HISTOGRAM);
   DCHECK(histogram->HasConstructorArguments(ranges[1], ranges.back(),
                                             ranges.size()));
   return histogram;
 }
 Histogram::ClassType CustomHistogram::histogram_type() const {
   return CUSTOM_HISTOGRAM;
 }
 CustomHistogram::CustomHistogram(const std::string& name,
                                  const std::vector<Sample>& custom_ranges)
     : Histogram(name, custom_ranges[1], custom_ranges.back(),
                 custom_ranges.size()) {
   DCHECK_GT(custom_ranges.size(), 1u);
   DCHECK_EQ(custom_ranges[0], 0);
 }
 void CustomHistogram::InitializedCustomBucketRange(
     const std::vector<Sample>& custom_ranges) {
   DCHECK_GT(custom_ranges.size(), 1u);
   DCHECK_EQ(custom_ranges[0], 0);
   DCHECK_LE(custom_ranges.size(), bucket_count());
   for (size_t index = 0; index < custom_ranges.size(); ++index)
     SetBucketRange(index, custom_ranges[index]);
   ResetRangeChecksum();
 }
 double CustomHistogram::GetBucketSize(Count current, size_t i) const {
   return 1;
 }
 //------------------------------------------------------------------------------
 // The next section handles global (central) support for all histograms, as well
 // as startup/teardown of this service.
 //------------------------------------------------------------------------------
 // This singleton instance should be started during the single threaded portion
 // of main(), and hence it is not thread safe.  It initializes globals to
 // provide support for all future calls.
 StatisticsRecorder::StatisticsRecorder() {
   DCHECK(!histograms_);
   if (lock_ == NULL) {
     // This will leak on purpose. It's the only way to make sure we won't race
     // against the static uninitialization of the module while one of our
     // static methods relying on the lock get called at an inappropriate time
     // during the termination phase. Since it's a static data member, we will
     // leak one per process, which would be similar to the instance allocated
     // during static initialization and released only on  process termination.
     lock_ = new base::Lock;
   }
   base::AutoLock auto_lock(*lock_);
   histograms_ = new HistogramMap;
 }
 StatisticsRecorder::~StatisticsRecorder() {
   DCHECK(histograms_ && lock_);
   if (dump_on_exit_) {
     std::string output;
     WriteGraph("", &output);
     CHROMIUM_LOG(INFO) << output;
   }
   // Clean up.
   HistogramMap* histograms = NULL;
   {
     base::AutoLock auto_lock(*lock_);
     histograms = histograms_;
     histograms_ = NULL;
     for (HistogramMap::iterator it = histograms->begin();
          histograms->end() != it;
          ++it) {
       // No other clients permanently hold Histogram references, so we
       // have the only one and it is safe to delete it.
       delete it->second;
     }
   }
   delete histograms;
   // We don't delete lock_ on purpose to avoid having to properly protect
   // against it going away after we checked for NULL in the static methods.
 }
 // static
 bool StatisticsRecorder::IsActive() {
   if (lock_ == NULL)
     return false;
   base::AutoLock auto_lock(*lock_);
   return NULL != histograms_;
 }
 Histogram* StatisticsRecorder::RegisterOrDeleteDuplicate(Histogram* histogram) {
   DCHECK(histogram->HasValidRangeChecksum());
   if (lock_ == NULL)
     return histogram;
   base::AutoLock auto_lock(*lock_);
   if (!histograms_)
     return histogram;
   const std::string name = histogram->histogram_name();
   HistogramMap::iterator it = histograms_->find(name);
   // Avoid overwriting a previous registration.
   if (histograms_->end() == it) {
     (*histograms_)[name] = histogram;
   } else {
     delete histogram;  // We already have one by this name.
     histogram = it->second;
   }
   return histogram;
 }
 // static
 void StatisticsRecorder::WriteHTMLGraph(const std::string& query,
                                         std::string* output) {
   if (!IsActive())
     return;
   output->append("<html><head><title>About Histograms");
   if (!query.empty())
     output->append(" - " + query);
   output->append("</title>"
                  // We'd like the following no-cache... but it doesn't work.
                  // "<META HTTP-EQUIV=\"Pragma\" CONTENT=\"no-cache\">"
                  "</head><body>");
   Histograms snapshot;
   GetSnapshot(query, &snapshot);
   for (Histograms::iterator it = snapshot.begin();
        it != snapshot.end();
        ++it) {
     (*it)->WriteHTMLGraph(output);
     output->append("<br><hr><br>");
   }
   output->append("</body></html>");
 }
 // static
 void StatisticsRecorder::WriteGraph(const std::string& query,
                                     std::string* output) {
   if (!IsActive())
     return;
   if (query.length())
     StringAppendF(output, "Collections of histograms for %s\n", query.c_str());
   else
     output->append("Collections of all histograms\n");
   Histograms snapshot;
   GetSnapshot(query, &snapshot);
   for (Histograms::iterator it = snapshot.begin();
        it != snapshot.end();
        ++it) {
     (*it)->WriteAscii(true, "\n", output);
     output->append("\n");
   }
 }
 // static
 void StatisticsRecorder::GetHistograms(Histograms* output) {
   if (lock_ == NULL)
     return;
   base::AutoLock auto_lock(*lock_);
   if (!histograms_)
     return;
   for (HistogramMap::iterator it = histograms_->begin();
        histograms_->end() != it;
        ++it) {
     DCHECK_EQ(it->first, it->second->histogram_name());
     output->push_back(it->second);
   }
 }
 bool StatisticsRecorder::FindHistogram(const std::string& name,
                                        Histogram** histogram) {
   if (lock_ == NULL)
     return false;
   base::AutoLock auto_lock(*lock_);
   if (!histograms_)
     return false;
   HistogramMap::iterator it = histograms_->find(name);
   if (histograms_->end() == it)
     return false;
   *histogram = it->second;
   return true;
 }
 // private static
 void StatisticsRecorder::GetSnapshot(const std::string& query,
                                      Histograms* snapshot) {
   if (lock_ == NULL)
     return;
   base::AutoLock auto_lock(*lock_);
   if (!histograms_)
     return;
   for (HistogramMap::iterator it = histograms_->begin();
        histograms_->end() != it;
        ++it) {
     if (it->first.find(query) != std::string::npos)
       snapshot->push_back(it->second);
   }
 }
 // static
 StatisticsRecorder::HistogramMap* StatisticsRecorder::histograms_ = NULL;
 // static
 base::Lock* StatisticsRecorder::lock_ = NULL;
 // static
 bool StatisticsRecorder::dump_on_exit_ = false;
 }  // namespace base

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ipc/chromium/src/base/histogram.cc@6474c204b198 (annotated)

ipc/chromium/src/base/histogram.cc