Revert of Revert of Componentize HistoryURLProvider/ScoredHistoryMatch.

chrome/browser/autocomplete/scored_history_match.cc

Index: chrome/browser/autocomplete/scored_history_match.cc
diff --git a/chrome/browser/autocomplete/scored_history_match.cc b/chrome/browser/autocomplete/scored_history_match.cc
deleted file mode 100644
index d90f930af7126127113fdb591d1c417c233364a3..0000000000000000000000000000000000000000
--- a/chrome/browser/autocomplete/scored_history_match.cc
+++ /dev/null
@@ -1,699 +0,0 @@
-// Copyright (c) 2012 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.
-
-#include "chrome/browser/autocomplete/scored_history_match.h"
-
-#include <math.h>
-
-#include <algorithm>
-#include <vector>
-
-#include "base/logging.h"
-#include "base/numerics/safe_conversions.h"
-#include "base/strings/string_number_conversions.h"
-#include "base/strings/string_split.h"
-#include "base/strings/string_util.h"
-#include "base/strings/utf_offset_string_conversions.h"
-#include "base/strings/utf_string_conversions.h"
-#include "chrome/browser/autocomplete/history_url_provider.h"
-#include "components/bookmarks/browser/bookmark_utils.h"
-#include "components/omnibox/omnibox_field_trial.h"
-#include "components/omnibox/url_prefix.h"
-
-namespace {
-
-// The number of days of recency scores to precompute.
-const int kDaysToPrecomputeRecencyScoresFor = 366;
-
-// The number of raw term score buckets use; raw term scores greater this are
-// capped at the score of the largest bucket.
-const int kMaxRawTermScore = 30;
-
-// Pre-computed information to speed up calculating recency scores.
-// |days_ago_to_recency_score| is a simple array mapping how long ago a page was
-// visited (in days) to the recency score we should assign it.  This allows easy
-// lookups of scores without requiring math. This is initialized by
-// InitDaysAgoToRecencyScoreArray called by
-// ScoredHistoryMatch::Init().
-float days_ago_to_recency_score[kDaysToPrecomputeRecencyScoresFor];
-
-// Pre-computed information to speed up calculating topicality scores.
-// |raw_term_score_to_topicality_score| is a simple array mapping how raw terms
-// scores (a weighted sum of the number of hits for the term, weighted by how
-// important the hit is: hostname, path, etc.) to the topicality score we should
-// assign it.  This allows easy lookups of scores without requiring math. This
-// is initialized by InitRawTermScoreToTopicalityScoreArray() called from
-// ScoredHistoryMatch::Init().
-float raw_term_score_to_topicality_score[kMaxRawTermScore];
-
-// Precalculates raw_term_score_to_topicality_score, used in
-// GetTopicalityScore().
-void InitRawTermScoreToTopicalityScoreArray() {
-  for (int term_score = 0; term_score < kMaxRawTermScore; ++term_score) {
-    float topicality_score;
-    if (term_score < 10) {
-      // If the term scores less than 10 points (no full-credit hit, or
-      // no combination of hits that score that well), then the topicality
-      // score is linear in the term score.
-      topicality_score = 0.1 * term_score;
-    } else {
-      // For term scores of at least ten points, pass them through a log
-      // function so a score of 10 points gets a 1.0 (to meet up exactly
-      // with the linear component) and increases logarithmically until
-      // maxing out at 30 points, with computes to a score around 2.1.
-      topicality_score = (1.0 + 2.25 * log10(0.1 * term_score));
-    }
-    raw_term_score_to_topicality_score[term_score] = topicality_score;
-  }
-}
-
-// Pre-calculates days_ago_to_recency_score, used in GetRecencyScore().
-void InitDaysAgoToRecencyScoreArray() {
-  for (int days_ago = 0; days_ago < kDaysToPrecomputeRecencyScoresFor;
-       days_ago++) {
-    int unnormalized_recency_score;
-    if (days_ago <= 4) {
-      unnormalized_recency_score = 100;
-    } else if (days_ago <= 14) {
-      // Linearly extrapolate between 4 and 14 days so 14 days has a score
-      // of 70.
-      unnormalized_recency_score = 70 + (14 - days_ago) * (100 - 70) / (14 - 4);
-    } else if (days_ago <= 31) {
-      // Linearly extrapolate between 14 and 31 days so 31 days has a score
-      // of 50.
-      unnormalized_recency_score = 50 + (31 - days_ago) * (70 - 50) / (31 - 14);
-    } else if (days_ago <= 90) {
-      // Linearly extrapolate between 30 and 90 days so 90 days has a score
-      // of 30.
-      unnormalized_recency_score = 30 + (90 - days_ago) * (50 - 30) / (90 - 30);
-    } else {
-      // Linearly extrapolate between 90 and 365 days so 365 days has a score
-      // of 10.
-      unnormalized_recency_score =
-          10 + (365 - days_ago) * (20 - 10) / (365 - 90);
-    }
-    days_ago_to_recency_score[days_ago] = unnormalized_recency_score / 100.0;
-    if (days_ago > 0) {
-      DCHECK_LE(days_ago_to_recency_score[days_ago],
-                days_ago_to_recency_score[days_ago - 1]);
-    }
-  }
-}
-
-}  // namespace
-
-// static
-const size_t ScoredHistoryMatch::kMaxVisitsToScore = 10;
-bool ScoredHistoryMatch::also_do_hup_like_scoring_ = false;
-int ScoredHistoryMatch::bookmark_value_ = 1;
-bool ScoredHistoryMatch::fix_frequency_bugs_ = false;
-bool ScoredHistoryMatch::allow_tld_matches_ = false;
-bool ScoredHistoryMatch::allow_scheme_matches_ = false;
-size_t ScoredHistoryMatch::num_title_words_to_allow_ = 10u;
-bool ScoredHistoryMatch::hqp_experimental_scoring_enabled_ = false;
-float ScoredHistoryMatch::topicality_threshold_ = -1;
-std::vector<ScoredHistoryMatch::ScoreMaxRelevance>*
-    ScoredHistoryMatch::hqp_relevance_buckets_ = nullptr;
-
-ScoredHistoryMatch::ScoredHistoryMatch()
-    : ScoredHistoryMatch(history::URLRow(),
-                         VisitInfoVector(),
-                         std::string(),
-                         base::string16(),
-                         String16Vector(),
-                         WordStarts(),
-                         RowWordStarts(),
-                         false,
-                         base::Time::Max()) {
-}
-
-ScoredHistoryMatch::ScoredHistoryMatch(
-    const history::URLRow& row,
-    const VisitInfoVector& visits,
-    const std::string& languages,
-    const base::string16& lower_string,
-    const String16Vector& terms_vector,
-    const WordStarts& terms_to_word_starts_offsets,
-    const RowWordStarts& word_starts,
-    bool is_url_bookmarked,
-    base::Time now)
-    : HistoryMatch(row, 0, false, false), raw_score(0), can_inline(false) {
-  // NOTE: Call Init() before doing any validity checking to ensure that the
-  // class is always initialized after an instance has been constructed. In
-  // particular, this ensures that the class is initialized after an instance
-  // has been constructed via the no-args constructor.
-  ScoredHistoryMatch::Init();
-
-  GURL gurl = row.url();
-  if (!gurl.is_valid())
-    return;
-
-  // Figure out where each search term appears in the URL and/or page title
-  // so that we can score as well as provide autocomplete highlighting.
-  base::OffsetAdjuster::Adjustments adjustments;
-  base::string16 url =
-      bookmarks::CleanUpUrlForMatching(gurl, languages, &adjustments);
-  base::string16 title = bookmarks::CleanUpTitleForMatching(row.title());
-  int term_num = 0;
-  for (const auto& term : terms_vector) {
-    TermMatches url_term_matches = MatchTermInString(term, url, term_num);
-    TermMatches title_term_matches = MatchTermInString(term, title, term_num);
-    if (url_term_matches.empty() && title_term_matches.empty()) {
-      // A term was not found in either URL or title - reject.
-      return;
-    }
-    url_matches.insert(url_matches.end(), url_term_matches.begin(),
-                       url_term_matches.end());
-    title_matches.insert(title_matches.end(), title_term_matches.begin(),
-                         title_term_matches.end());
-    ++term_num;
-  }
-
-  // Sort matches by offset and eliminate any which overlap.
-  // TODO(mpearson): Investigate whether this has any meaningful
-  // effect on scoring.  (It's necessary at some point: removing
-  // overlaps and sorting is needed to decide what to highlight in the
-  // suggestion string.  But this sort and de-overlap doesn't have to
-  // be done before scoring.)
-  url_matches = SortAndDeoverlapMatches(url_matches);
-  title_matches = SortAndDeoverlapMatches(title_matches);
-
-  // We can inline autocomplete a match if:
-  //  1) there is only one search term
-  //  2) AND the match begins immediately after one of the prefixes in
-  //     URLPrefix such as http://www and https:// (note that one of these
-  //     is the empty prefix, for cases where the user has typed the scheme)
-  //  3) AND the search string does not end in whitespace (making it look to
-  //     the IMUI as though there is a single search term when actually there
-  //     is a second, empty term).
-  // |best_inlineable_prefix| stores the inlineable prefix computed in
-  // clause (2) or NULL if no such prefix exists.  (The URL is not inlineable.)
-  // Note that using the best prefix here means that when multiple
-  // prefixes match, we'll choose to inline following the longest one.
-  // For a URL like "http://www.washingtonmutual.com", this means
-  // typing "w" will inline "ashington..." instead of "ww.washington...".
-  if (!url_matches.empty() && (terms_vector.size() == 1) &&
-      !IsWhitespace(*lower_string.rbegin())) {
-    const base::string16 gurl_spec = base::UTF8ToUTF16(gurl.spec());
-    const URLPrefix* best_inlineable_prefix =
-        URLPrefix::BestURLPrefix(gurl_spec, terms_vector[0]);
-    if (best_inlineable_prefix) {
-      // When inline autocompleting this match, we're going to use the part of
-      // the URL following the end of the matching text.  However, it's possible
-      // that FormatUrl(), when formatting this suggestion for display,
-      // mucks with the text.  We need to ensure that the text we're thinking
-      // about highlighting isn't in the middle of a mucked sequence.  In
-      // particular, for the omnibox input of "x" or "xn", we may get a match
-      // in a punycoded domain name such as http://www.xn--blahblah.com/.
-      // When FormatUrl() processes the xn--blahblah part of the hostname, it'll
-      // transform the whole thing into a series of unicode characters.  It's
-      // impossible to give the user an inline autocompletion of the text
-      // following "x" or "xn" in this case because those characters no longer
-      // exist in the displayed URL string.
-      size_t offset =
-        best_inlineable_prefix->prefix.length() + terms_vector[0].length();
-      base::OffsetAdjuster::UnadjustOffset(adjustments, &offset);
-      if (offset != base::string16::npos) {
-        // Initialize innermost_match.
-        // The idea here is that matches that occur in the scheme or
-        // "www." are worse than matches which don't.  For the URLs
-        // "http://www.google.com" and "http://wellsfargo.com", we want
-        // the omnibox input "w" to cause the latter URL to rank higher
-        // than the former.  Note that this is not the same as checking
-        // whether one match's inlinable prefix has more components than
-        // the other match's, since in this example, both matches would
-        // have an inlinable prefix of "http://", which is one component.
-        //
-        // Instead, we look for the overall best (i.e., most components)
-        // prefix of the current URL, and then check whether the inlinable
-        // prefix has that many components.  If it does, this is an
-        // "innermost" match, and should be boosted.  In the example
-        // above, the best prefixes for the two URLs have two and one
-        // components respectively, while the inlinable prefixes each
-        // have one component; this means the first match is not innermost
-        // and the second match is innermost, resulting in us boosting the
-        // second match.
-        //
-        // Now, the code that implements this.
-        // The deepest prefix for this URL regardless of where the match is.
-        const URLPrefix* best_prefix =
-            URLPrefix::BestURLPrefix(gurl_spec, base::string16());
-        DCHECK(best_prefix);
-        // If the URL is inlineable, we must have a match.  Note the prefix that
-        // makes it inlineable may be empty.
-        can_inline = true;
-        innermost_match = (best_inlineable_prefix->num_components ==
-                           best_prefix->num_components);
-      }
-    }
-  }
-
-  const float topicality_score = GetTopicalityScore(
-      terms_vector.size(), url, terms_to_word_starts_offsets, word_starts);
-  const float frequency_score = GetFrequency(now, is_url_bookmarked, visits);
-  raw_score = base::saturated_cast<int>(GetFinalRelevancyScore(
-      topicality_score, frequency_score, *hqp_relevance_buckets_));
-
-  if (also_do_hup_like_scoring_ && can_inline) {
-    // HistoryURL-provider-like scoring gives any match that is
-    // capable of being inlined a certain minimum score.  Some of these
-    // are given a higher score that lets them be shown in inline.
-    // This test here derives from the test in
-    // HistoryURLProvider::PromoteMatchForInlineAutocomplete().
-    const bool promote_to_inline =
-        (row.typed_count() > 1) || (IsHostOnly() && (row.typed_count() == 1));
-    int hup_like_score =
-        promote_to_inline
-            ? HistoryURLProvider::kScoreForBestInlineableResult
-            : HistoryURLProvider::kBaseScoreForNonInlineableResult;
-
-    // Also, if the user types the hostname of a host with a typed
-    // visit, then everything from that host get given inlineable scores
-    // (because the URL-that-you-typed will go first and everything
-    // else will be assigned one minus the previous score, as coded
-    // at the end of HistoryURLProvider::DoAutocomplete().
-    if (base::UTF8ToUTF16(gurl.host()) == terms_vector[0])
-      hup_like_score = HistoryURLProvider::kScoreForBestInlineableResult;
-
-    // HistoryURLProvider has the function PromoteOrCreateShorterSuggestion()
-    // that's meant to promote prefixes of the best match (if they've
-    // been visited enough related to the best match) or
-    // create/promote host-only suggestions (even if they've never
-    // been typed).  The code is complicated and we don't try to
-    // duplicate the logic here.  Instead, we handle a simple case: in
-    // low-typed-count ranges, give host-only matches (i.e.,
-    // http://www.foo.com/ vs. http://www.foo.com/bar.html) a boost so
-    // that the host-only match outscores all the other matches that
-    // would normally have the same base score.  This behavior is not
-    // identical to what happens in HistoryURLProvider even in these
-    // low typed count ranges--sometimes it will create/promote when
-    // this test does not (indeed, we cannot create matches like HUP
-    // can) and vice versa--but the underlying philosophy is similar.
-    if (!promote_to_inline && IsHostOnly())
-      hup_like_score++;
-
-    // All the other logic to goes into hup-like-scoring happens in
-    // the tie-breaker case of MatchScoreGreater().
-
-    // Incorporate hup_like_score into raw_score.
-    raw_score = std::max(raw_score, hup_like_score);
-  }
-
-  // Now that we're done processing this entry, correct the offsets of the
-  // matches in |url_matches| so they point to offsets in the original URL
-  // spec, not the cleaned-up URL string that we used for matching.
-  std::vector<size_t> offsets = OffsetsFromTermMatches(url_matches);
-  base::OffsetAdjuster::UnadjustOffsets(adjustments, &offsets);
-  url_matches = ReplaceOffsetsInTermMatches(url_matches, offsets);
-}
-
-ScoredHistoryMatch::~ScoredHistoryMatch() {
-}
-
-// Comparison function for sorting ScoredMatches by their scores with
-// intelligent tie-breaking.
-bool ScoredHistoryMatch::MatchScoreGreater(const ScoredHistoryMatch& m1,
-                                           const ScoredHistoryMatch& m2) {
-  if (m1.raw_score != m2.raw_score)
-    return m1.raw_score > m2.raw_score;
-
-  // This tie-breaking logic is inspired by / largely copied from the
-  // ordering logic in history_url_provider.cc CompareHistoryMatch().
-
-  // A URL that has been typed at all is better than one that has never been
-  // typed.  (Note "!"s on each side.)
-  if (!m1.url_info.typed_count() != !m2.url_info.typed_count())
-    return m1.url_info.typed_count() > m2.url_info.typed_count();
-
-  // Innermost matches (matches after any scheme or "www.") are better than
-  // non-innermost matches.
-  if (m1.innermost_match != m2.innermost_match)
-    return m1.innermost_match;
-
-  // URLs that have been typed more often are better.
-  if (m1.url_info.typed_count() != m2.url_info.typed_count())
-    return m1.url_info.typed_count() > m2.url_info.typed_count();
-
-  // For URLs that have each been typed once, a host (alone) is better
-  // than a page inside.
-  if (m1.url_info.typed_count() == 1) {
-    if (m1.IsHostOnly() != m2.IsHostOnly())
-      return m1.IsHostOnly();
-  }
-
-  // URLs that have been visited more often are better.
-  if (m1.url_info.visit_count() != m2.url_info.visit_count())
-    return m1.url_info.visit_count() > m2.url_info.visit_count();
-
-  // URLs that have been visited more recently are better.
-  return m1.url_info.last_visit() > m2.url_info.last_visit();
-}
-
-// static
-TermMatches ScoredHistoryMatch::FilterTermMatchesByWordStarts(
-    const TermMatches& term_matches,
-    const WordStarts& terms_to_word_starts_offsets,
-    const WordStarts& word_starts,
-    size_t start_pos,
-    size_t end_pos) {
-  // Return early if no filtering is needed.
-  if (start_pos == std::string::npos)
-    return term_matches;
-  TermMatches filtered_matches;
-  WordStarts::const_iterator next_word_starts = word_starts.begin();
-  WordStarts::const_iterator end_word_starts = word_starts.end();
-  for (const auto& term_match : term_matches) {
-    const size_t term_offset =
-        terms_to_word_starts_offsets[term_match.term_num];
-    // Advance next_word_starts until it's >= the position of the term we're
-    // considering (adjusted for where the word begins within the term).
-    while ((next_word_starts != end_word_starts) &&
-           (*next_word_starts < (term_match.offset + term_offset)))
-      ++next_word_starts;
-    // Add the match if it's before the position we start filtering at or
-    // after the position we stop filtering at (assuming we have a position
-    // to stop filtering at) or if it's at a word boundary.
-    if ((term_match.offset < start_pos) ||
-        ((end_pos != std::string::npos) && (term_match.offset >= end_pos)) ||
-        ((next_word_starts != end_word_starts) &&
-         (*next_word_starts == term_match.offset + term_offset)))
-      filtered_matches.push_back(term_match);
-  }
-  return filtered_matches;
-}
-
-// static
-void ScoredHistoryMatch::Init() {
-  static bool initialized = false;
-
-  if (initialized)
-    return;
-
-  initialized = true;
-  also_do_hup_like_scoring_ = OmniboxFieldTrial::HQPAlsoDoHUPLikeScoring();
-  bookmark_value_ = OmniboxFieldTrial::HQPBookmarkValue();
-  fix_frequency_bugs_ = OmniboxFieldTrial::HQPFixFrequencyScoringBugs();
-  allow_tld_matches_ = OmniboxFieldTrial::HQPAllowMatchInTLDValue();
-  allow_scheme_matches_ = OmniboxFieldTrial::HQPAllowMatchInSchemeValue();
-  num_title_words_to_allow_ = OmniboxFieldTrial::HQPNumTitleWordsToAllow();
-
-  InitRawTermScoreToTopicalityScoreArray();
-  InitDaysAgoToRecencyScoreArray();
-  InitHQPExperimentalParams();
-}
-
-float ScoredHistoryMatch::GetTopicalityScore(
-    const int num_terms,
-    const base::string16& url,
-    const WordStarts& terms_to_word_starts_offsets,
-    const RowWordStarts& word_starts) {
-  // A vector that accumulates per-term scores.  The strongest match--a
-  // match in the hostname at a word boundary--is worth 10 points.
-  // Everything else is less.  In general, a match that's not at a word
-  // boundary is worth about 1/4th or 1/5th of a match at the word boundary
-  // in the same part of the URL/title.
-  DCHECK_GT(num_terms, 0);
-  std::vector<int> term_scores(num_terms, 0);
-  WordStarts::const_iterator next_word_starts =
-      word_starts.url_word_starts_.begin();
-  WordStarts::const_iterator end_word_starts =
-      word_starts.url_word_starts_.end();
-  const size_t question_mark_pos = url.find('?');
-  const size_t colon_pos = url.find(':');
-  // The + 3 skips the // that probably appears in the protocol
-  // after the colon.  If the protocol doesn't have two slashes after
-  // the colon, that's okay--all this ends up doing is starting our
-  // search for the next / a few characters into the hostname.  The
-  // only times this can cause problems is if we have a protocol without
-  // a // after the colon and the hostname is only one or two characters.
-  // This isn't worth worrying about.
-  const size_t end_of_hostname_pos = (colon_pos != std::string::npos)
-                                         ? url.find('/', colon_pos + 3)
-                                         : url.find('/');
-  size_t last_part_of_hostname_pos = (end_of_hostname_pos != std::string::npos)
-                                         ? url.rfind('.', end_of_hostname_pos)
-                                         : url.rfind('.');
-  // Loop through all URL matches and score them appropriately.
-  // First, filter all matches not at a word boundary and in the path (or
-  // later).
-  url_matches = FilterTermMatchesByWordStarts(
-      url_matches, terms_to_word_starts_offsets, word_starts.url_word_starts_,
-      end_of_hostname_pos, std::string::npos);
-  if (colon_pos != std::string::npos) {
-    // Also filter matches not at a word boundary and in the scheme.
-    url_matches = FilterTermMatchesByWordStarts(
-        url_matches, terms_to_word_starts_offsets, word_starts.url_word_starts_,
-        0, colon_pos);
-  }
-  for (const auto& url_match : url_matches) {
-    const size_t term_offset = terms_to_word_starts_offsets[url_match.term_num];
-    // Advance next_word_starts until it's >= the position of the term we're
-    // considering (adjusted for where the word begins within the term).
-    while ((next_word_starts != end_word_starts) &&
-           (*next_word_starts < (url_match.offset + term_offset))) {
-      ++next_word_starts;
-    }
-    const bool at_word_boundary =
-        (next_word_starts != end_word_starts) &&
-        (*next_word_starts == url_match.offset + term_offset);
-    if ((question_mark_pos != std::string::npos) &&
-        (url_match.offset > question_mark_pos)) {
-      // The match is in a CGI ?... fragment.
-      DCHECK(at_word_boundary);
-      term_scores[url_match.term_num] += 5;
-    } else if ((end_of_hostname_pos != std::string::npos) &&
-               (url_match.offset > end_of_hostname_pos)) {
-      // The match is in the path.
-      DCHECK(at_word_boundary);
-      term_scores[url_match.term_num] += 8;
-    } else if ((colon_pos == std::string::npos) ||
-               (url_match.offset > colon_pos)) {
-      // The match is in the hostname.
-      if ((last_part_of_hostname_pos == std::string::npos) ||
-          (url_match.offset < last_part_of_hostname_pos)) {
-        // Either there are no dots in the hostname or this match isn't
-        // the last dotted component.
-        term_scores[url_match.term_num] += at_word_boundary ? 10 : 2;
-      } else {
-        // The match is in the last part of a dotted hostname (usually this
-        // is the top-level domain .com, .net, etc.).
-        if (allow_tld_matches_)
-          term_scores[url_match.term_num] += at_word_boundary ? 10 : 0;
-      }
-    } else {
-      // The match is in the protocol (a.k.a. scheme).
-      // Matches not at a word boundary should have been filtered already.
-      DCHECK(at_word_boundary);
-      match_in_scheme = true;
-      if (allow_scheme_matches_)
-        term_scores[url_match.term_num] += 10;
-    }
-  }
-  // Now do the analogous loop over all matches in the title.
-  next_word_starts = word_starts.title_word_starts_.begin();
-  end_word_starts = word_starts.title_word_starts_.end();
-  size_t word_num = 0;
-  title_matches = FilterTermMatchesByWordStarts(
-      title_matches, terms_to_word_starts_offsets,
-      word_starts.title_word_starts_, 0, std::string::npos);
-  for (const auto& title_match : title_matches) {
-    const size_t term_offset =
-        terms_to_word_starts_offsets[title_match.term_num];
-    // Advance next_word_starts until it's >= the position of the term we're
-    // considering (adjusted for where the word begins within the term).
-    while ((next_word_starts != end_word_starts) &&
-           (*next_word_starts < (title_match.offset + term_offset))) {
-      ++next_word_starts;
-      ++word_num;
-    }
-    if (word_num >= num_title_words_to_allow_)
-      break;  // only count the first ten words
-    DCHECK(next_word_starts != end_word_starts);
-    DCHECK_EQ(*next_word_starts, title_match.offset + term_offset)
-        << "not at word boundary";
-    term_scores[title_match.term_num] += 8;
-  }
-  // TODO(mpearson): Restore logic for penalizing out-of-order matches.
-  // (Perhaps discount them by 0.8?)
-  // TODO(mpearson): Consider: if the earliest match occurs late in the string,
-  // should we discount it?
-  // TODO(mpearson): Consider: do we want to score based on how much of the
-  // input string the input covers?  (I'm leaning toward no.)
-
-  // Compute the topicality_score as the sum of transformed term_scores.
-  float topicality_score = 0;
-  for (int term_score : term_scores) {
-    // Drop this URL if it seems like a term didn't appear or, more precisely,
-    // didn't appear in a part of the URL or title that we trust enough
-    // to give it credit for.  For instance, terms that appear in the middle
-    // of a CGI parameter get no credit.  Almost all the matches dropped
-    // due to this test would look stupid if shown to the user.
-    if (term_score == 0)
-      return 0;
-    topicality_score += raw_term_score_to_topicality_score[std::min(
-        term_score, kMaxRawTermScore - 1)];
-  }
-  // TODO(mpearson): If there are multiple terms, consider taking the
-  // geometric mean of per-term scores rather than the arithmetic mean.
-
-  const float final_topicality_score = topicality_score / num_terms;
-
-  // Demote the URL if the topicality score is less than threshold.
-  if (hqp_experimental_scoring_enabled_ &&
-      (final_topicality_score < topicality_threshold_)) {
-    return 0.0;
-  }
-
-  return final_topicality_score;
-}
-
-float ScoredHistoryMatch::GetRecencyScore(int last_visit_days_ago) const {
-  // Lookup the score in days_ago_to_recency_score, treating
-  // everything older than what we've precomputed as the oldest thing
-  // we've precomputed.  The std::max is to protect against corruption
-  // in the database (in case last_visit_days_ago is negative).
-  return days_ago_to_recency_score[std::max(
-      std::min(last_visit_days_ago, kDaysToPrecomputeRecencyScoresFor - 1), 0)];
-}
-
-float ScoredHistoryMatch::GetFrequency(const base::Time& now,
-                                       const bool bookmarked,
-                                       const VisitInfoVector& visits) const {
-  // Compute the weighted average |value_of_transition| over the last at
-  // most kMaxVisitsToScore visits, where each visit is weighted using
-  // GetRecencyScore() based on how many days ago it happened.  Use
-  // kMaxVisitsToScore as the denominator for the average regardless of
-  // how many visits there were in order to penalize a match that has
-  // fewer visits than kMaxVisitsToScore.
-  float summed_visit_points = 0;
-  const size_t max_visit_to_score =
-      std::min(visits.size(), ScoredHistoryMatch::kMaxVisitsToScore);
-  for (size_t i = 0; i < max_visit_to_score; ++i) {
-    const ui::PageTransition page_transition = fix_frequency_bugs_ ?
-      ui::PageTransitionStripQualifier(visits[i].second) : visits[i].second;
-    int value_of_transition =
-        (page_transition == ui::PAGE_TRANSITION_TYPED) ? 20 : 1;
-    if (bookmarked)
-      value_of_transition = std::max(value_of_transition, bookmark_value_);
-    const float bucket_weight =
-        GetRecencyScore((now - visits[i].first).InDays());
-    summed_visit_points += (value_of_transition * bucket_weight);
-  }
-  if (fix_frequency_bugs_)
-    return summed_visit_points / ScoredHistoryMatch::kMaxVisitsToScore;
-  return visits.size() * summed_visit_points /
-      ScoredHistoryMatch::kMaxVisitsToScore;
-}
-
-// static
-float ScoredHistoryMatch::GetFinalRelevancyScore(
-    float topicality_score,
-    float frequency_score,
-    const std::vector<ScoreMaxRelevance>& hqp_relevance_buckets) {
-  DCHECK(hqp_relevance_buckets.size() > 0);
-  DCHECK_EQ(hqp_relevance_buckets[0].first, 0.0);
-
-  if (topicality_score == 0)
-    return 0;
-  // Here's how to interpret intermediate_score: Suppose the omnibox
-  // has one input term.  Suppose we have a URL for which the omnibox
-  // input term has a single URL hostname hit at a word boundary.  (This
-  // implies topicality_score = 1.0.).  Then the intermediate_score for
-  // this URL will depend entirely on the frequency_score with
-  // this interpretation:
-  // - a single typed visit more than three months ago, no other visits -> 0.2
-  // - a visit every three days, no typed visits -> 0.706
-  // - a visit every day, no typed visits -> 0.916
-  // - a single typed visit yesterday, no other visits -> 2.0
-  // - a typed visit once a week -> 11.77
-  // - a typed visit every three days -> 14.12
-  // - at least ten typed visits today -> 20.0 (maximum score)
-  //
-  // The below code maps intermediate_score to the range [0, 1399].
-  // For example:
-  // HQP default scoring buckets: "0.0:400,1.5:600,12.0:1300,20.0:1399"
-  // We will linearly interpolate the scores between:
-  //      0 to 1.5    --> 400 to 600
-  //    1.5 to 12.0   --> 600 to 1300
-  //    12.0 to 20.0  --> 1300 to 1399
-  //       >= 20.0    --> 1399
-  //
-  // The score maxes out at 1399 (i.e., cannot beat a good inlineable result
-  // from HistoryURL provider).
-  const float intermediate_score = topicality_score * frequency_score;
-
-  // Find the threshold where intermediate score is greater than bucket.
-  size_t i = 1;
-  for (; i < hqp_relevance_buckets.size(); ++i) {
-    const ScoreMaxRelevance& hqp_bucket = hqp_relevance_buckets[i];
-    if (intermediate_score >= hqp_bucket.first) {
-      continue;
-    }
-    const ScoreMaxRelevance& previous_bucket = hqp_relevance_buckets[i - 1];
-    const float slope = ((hqp_bucket.second - previous_bucket.second) /
-                         (hqp_bucket.first - previous_bucket.first));
-    return (previous_bucket.second +
-            (slope * (intermediate_score - previous_bucket.first)));
-  }
-  // It will reach this stage when the score is > highest bucket score.
-  // Return the highest bucket score.
-  return hqp_relevance_buckets[i - 1].second;
-}
-
-// static
-void ScoredHistoryMatch::InitHQPExperimentalParams() {
-  // These are default HQP relevance scoring buckets.
-  // See GetFinalRelevancyScore() for details.
-  std::string hqp_relevance_buckets_str = "0.0:400,1.5:600,12.0:1300,20.0:1399";
-
-  // Fetch the experiment params if they are any.
-  hqp_experimental_scoring_enabled_ =
-      OmniboxFieldTrial::HQPExperimentalScoringEnabled();
-
-  if (hqp_experimental_scoring_enabled_) {
-    // Add the topicality threshold from experiment params.
-    float hqp_experimental_topicality_threhold =
-        OmniboxFieldTrial::HQPExperimentalTopicalityThreshold();
-    topicality_threshold_ = hqp_experimental_topicality_threhold;
-
-    // Add the HQP experimental scoring buckets.
-    std::string hqp_experimental_scoring_buckets =
-        OmniboxFieldTrial::HQPExperimentalScoringBuckets();
-    if (!hqp_experimental_scoring_buckets.empty())
-      hqp_relevance_buckets_str = hqp_experimental_scoring_buckets;
-  }
-
-  // Parse the hqp_relevance_buckets_str string once and store them in vector
-  // which is easy to access.
-  hqp_relevance_buckets_ =
-      new std::vector<ScoredHistoryMatch::ScoreMaxRelevance>();
-
-  bool is_valid_bucket_str = GetHQPBucketsFromString(hqp_relevance_buckets_str,
-                                                     hqp_relevance_buckets_);
-  DCHECK(is_valid_bucket_str);
-}
-
-// static
-bool ScoredHistoryMatch::GetHQPBucketsFromString(
-    const std::string& buckets_str,
-    std::vector<ScoreMaxRelevance>* hqp_buckets) {
-  DCHECK(hqp_buckets != NULL);
-  DCHECK(!buckets_str.empty());
-
-  base::StringPairs kv_pairs;
-  if (base::SplitStringIntoKeyValuePairs(buckets_str, ':', ',', &kv_pairs)) {
-    for (base::StringPairs::const_iterator it = kv_pairs.begin();
-         it != kv_pairs.end(); ++it) {
-      ScoreMaxRelevance bucket;
-      bool is_valid_intermediate_score =
-          base::StringToDouble(it->first, &bucket.first);
-      DCHECK(is_valid_intermediate_score);
-      bool is_valid_hqp_score = base::StringToInt(it->second, &bucket.second);
-      DCHECK(is_valid_hqp_score);
-      hqp_buckets->push_back(bucket);
-    }
-    return true;
-  }
-  return false;
-}