下面的代码使用了很多标准库来为我们做一些常见的事情。我使用一个文件将单词收集到一个大字符串中。然后，我使用std::StringStream分隔空格上的单词，并将单个单词存储在std::Vector（一个数组，可管理其大小，并在需要时增长）中。为了获得良好的单词计数，还必须删除标点符号和大写，这是在sanitize_word()函数中完成的。最后，我将单词添加到一个映射中，其中单词是关键字，int是该单词出现的次数。最后，我打印地图以获得完整的字数。

我直接进行任何字符串解析的唯一地方是在sanitize函数中，它是使用恰当命名的erase/remove习惯用法完成的。在可能的情况下让标准库为我们做这些工作要简单得多。

input.txt的内容：

I must not fear. Fear is the mind-killer. Fear is the little-death that brings total obliteration. I will face my fear. I will permit it to pass over me and through me. And when it has gone past, I will turn the inner eye to see its path. Where the fear has gone, there will be nothing. Only I will remain.

#include <algorithm>
#include <cctype>
#include <fstream>
#include <iostream>
#include <map>
#include <sstream>
#include <string>
#include <vector>

// Removes puncuation marks and converts words to all lowercase
std::string sanitize_word(std::string word) {
  word.erase(std::remove_if(word.begin(), word.end(),
                            [punc = std::string(".,?!")](auto c) {
                              return punc.find(c) != std::string::npos;
                            }),
             word.end());
  for (auto& c : word) {
    c = std::tolower(c);
  }

  return word;
}

int main() {
  // Set up
  std::ifstream fin("input.txt");
  if (!fin) {
    std::cerr << "Error opening file...\n";
    return 1;
  }

  std::string phrases;
  for (std::string tmp; std::getline(fin, tmp);) {
    phrases += tmp;
  }
  fin.close();

  // Words are collected, now the part we care about
  std::stringstream strin(phrases);
  std::vector<std::string> words;
  for (std::string tmp; strin >> tmp;) {
    words.push_back(tmp);
  }

  for (auto& i : words) {
    i = sanitize_word(i);
  }

  // std::map's operator[]() function will create a new element in the map if it
  // doesn't already exist
  std::map<std::string, int> wordCounts;
  for (auto i : words) {
    ++wordCounts[i];
  }

  for (auto i : wordCounts) {
    std::cout << i.first << ": " << i.second << '\n';
  }
}

输出：

and: 2
be: 1
brings: 1
eye: 1
face: 1
fear: 5
gone: 2
has: 2
i: 5
inner: 1
is: 2
it: 2
its: 1
little-death: 1
me: 2
mind-killer: 1
must: 1
my: 1
not: 1
nothing: 1
obliteration: 1
only: 1
over: 1
pass: 1
past: 1
path: 1
permit: 1
remain: 1
see: 1
that: 1
the: 4
there: 1
through: 1
to: 2
total: 1
turn: 1
when: 1
where: 1
will: 5