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Merge LLVM r242069, make spell checking allocate less memory.
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@ -28,40 +28,42 @@ int EditDistance(const StringPiece& s1,
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// http://en.wikipedia.org/wiki/Levenshtein_distance
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//
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// Although the algorithm is typically described using an m x n
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// array, only two rows are used at a time, so this implementation
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// just keeps two separate vectors for those two rows.
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// array, only one row plus one element are used at a time, so this
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// implementation just keeps one vector for the row. To update one entry,
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// only the entries to the left, top, and top-left are needed. The left
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// entry is in row[x-1], the top entry is what's in row[x] from the last
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// iteration, and the top-left entry is stored in previous.
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int m = s1.len_;
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int n = s2.len_;
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vector<int> previous(n + 1);
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vector<int> current(n + 1);
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for (int i = 0; i <= n; ++i)
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previous[i] = i;
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vector<int> row(n + 1);
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for (int i = 1; i <= n; ++i)
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row[i] = i;
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for (int y = 1; y <= m; ++y) {
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current[0] = y;
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int best_this_row = current[0];
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row[0] = y;
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int best_this_row = row[0];
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int previous = y - 1;
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for (int x = 1; x <= n; ++x) {
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int old_row = row[x];
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if (allow_replacements) {
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current[x] = min(previous[x-1] + (s1.str_[y-1] == s2.str_[x-1] ? 0 : 1),
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min(current[x-1], previous[x])+1);
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row[x] = min(previous + (s1.str_[y - 1] == s2.str_[x - 1] ? 0 : 1),
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min(row[x - 1], row[x]) + 1);
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}
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else {
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if (s1.str_[y-1] == s2.str_[x-1])
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current[x] = previous[x-1];
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if (s1.str_[y - 1] == s2.str_[x - 1])
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row[x] = previous;
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else
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current[x] = min(current[x-1], previous[x]) + 1;
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row[x] = min(row[x - 1], row[x]) + 1;
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}
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best_this_row = min(best_this_row, current[x]);
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previous = old_row;
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best_this_row = min(best_this_row, row[x]);
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}
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if (max_edit_distance && best_this_row > max_edit_distance)
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return max_edit_distance + 1;
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current.swap(previous);
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}
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return previous[n];
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return row[n];
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}
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