## 1) Abridged problem statement

You are given the full text of a problem statement consisting of sentences ending with `.` (dot). Words are separated by single spaces; there is no space before a dot.

You may create alternative versions of the statement by applying **exactly one** negation in exactly one place:

- Insert the word **`not`** (exactly this lowercase spelling) after any word equal to (case-insensitive) `can`, `may`, `must`, `should`.
- Insert the word **`no`** (exactly this lowercase spelling) after any word equal to (case-insensitive) `is`, `are`. If immediately after that `is/are` there is an article `a` or `the` (case-insensitive), you must remove that article.

For every possible single negation (in natural order: sentence by sentence, and within a sentence from left to right), output the modified sentence (preserving original word casing for copied words). First output the number of such sentences, then list them, one per line.

Input size ≤ 1024 bytes.

---

## 2) Detailed editorial (how the solution works)

### Observations
- We must consider **each sentence independently**, but output all possibilities across the whole text.
- Only **one** negation is applied per output line.
- Candidate insertion positions are determined by matching specific trigger words/phrases case-insensitively:
  - `can/may/must/should` → insert `"not"` after that word.
  - `is/are` → insert `"no"` after that word, and possibly delete the next word if it is `a` or `the`.
- We must **not** change the spelling/case of the original words we output (except inserting the new word which must be exactly `not` or `no`).

### Step-by-step approach
1. **Read entire input text**
   - The input may contain newlines, but logically it’s a single stream of characters.
   - A simple approach: read all lines with `getline` and concatenate them with a space between lines (if needed). This matches the sample where lines wrap for readability.

2. **Split into sentences**
   - Sentences end at `.`.
   - Iterate over all characters and accumulate into `cur` until you meet `.`:
     - push `cur` to `sentences`
     - clear `cur`
   - The dot is not part of the sentence words; we will re-add it in output.

3. **Split each sentence into words**
   - Use whitespace splitting (e.g., `istringstream`) to obtain `words[]`.

4. **Scan for insertion points**
   - For each word position `i`:
     - If `words[i]` lowercased is in `{can, may, must, should}`:
       - Create an output sentence:
         - copy words `[0..i]`
         - add `"not"`
         - copy words `[i+1..end)`
     - Else if `words[i]` lowercased is in `{is, are}`:
       - Create an output sentence:
         - copy words `[0..i]`
         - add `"no"`
         - let `start = i+1`
         - if `start < n` and `words[start]` lowercased is `a` or `the`, increment `start` (skip that article)
         - copy words `[start..end)`

5. **Output**
   - Print the total number of generated sentences.
   - For each generated word list:
     - print words separated by single spaces
     - print a `.` at the end
   - Order requirement is naturally satisfied because we process sentences in order, and within each sentence positions from left to right.

### Complexity
- Input size is at most 1024 bytes, so everything is tiny.
- Time: `O(total_words)`; Memory: `O(total_words)` for storing results.

---

## 3) Provided C++ solution with detailed line-by-line comments

```cpp
#include <bits/stdc++.h>      // Pulls in essentially all standard headers (common in contests)

using namespace std;

// Pretty-print a pair as "first second"
template<typename T1, typename T2>
ostream& operator<<(ostream& out, const pair<T1, T2>& x) {
    return out << x.first << ' ' << x.second;
}

// Read a pair from input
template<typename T1, typename T2>
istream& operator>>(istream& in, pair<T1, T2>& x) {
    return in >> x.first >> x.second;
}

// Read a whole vector by reading each element sequentially
template<typename T>
istream& operator>>(istream& in, vector<T>& a) {
    for(auto& x: a) {         // iterate by reference so we can assign into elements
        in >> x;
    }
    return in;
};

// Print a vector with spaces (not used in final output here, but included as helper)
template<typename T>
ostream& operator<<(ostream& out, const vector<T>& a) {
    for(auto x: a) {
        out << x << ' ';
    }
    return out;
};

// Will hold the entire input text (all lines concatenated)
string text;

// Return a lowercase copy of a string (ASCII letters only are assumed)
string lower(const string& s) {
    string res;
    for(char c: s) {
        res += tolower(c);    // tolower converts to lowercase (locale-insensitive for ASCII)
    }
    return res;
}

// Split a string into words separated by whitespace
vector<string> split_words(const string& s) {
    istringstream is(s);      // stream that reads from string s
    vector<string> res;
    string w;
    while(is >> w) {          // operator>> automatically skips spaces and reads tokens
        res.push_back(w);
    }
    return res;
}

// Read the whole stdin as text; join lines with spaces as needed
void read() {
    string line;
    while(getline(cin, line)) {                    // read each line until EOF
        if(!text.empty() && text.back() != ' ') {  // ensure exactly one space between lines
            text += ' ';
        }
        text += line;                              // append the line content
    }
}

void solve() {
    // Approach:
    // 1) Split the whole text into sentences by '.'
    // 2) For each sentence, split into words
    // 3) For every word:
    //      - if it is can/may/must/should -> insert "not" after it
    //      - if it is is/are -> insert "no" after it and optionally remove following a/the
    // 4) Output all modified sentences in required order

    // Predicate: does this word allow inserting "not" after it?
    auto is_not_word = [](const string& s) {
        string lo = lower(s);
        return lo == "can" || lo == "may" || lo == "must" || lo == "should";
    };

    // Predicate: does this word allow inserting "no" after it?
    auto is_no_word = [](const string& s) {
        string lo = lower(s);
        return lo == "is" || lo == "are";
    };

    // Predicate: is this word an article that should be removed after inserting "no"?
    auto is_a_or_the = [](const string& s) {
        string lo = lower(s);
        return lo == "a" || lo == "the";
    };

    // Split into sentences by walking the characters and cutting on '.'
    vector<string> sentences;
    string cur;
    for(char c: text) {
        if(c == '.') {                // dot ends a sentence
            sentences.push_back(cur); // store sentence without the dot
            cur.clear();              // start building next sentence
        } else {
            cur += c;                 // accumulate sentence characters
        }
    }

    // results will store each generated variant as a list of words
    vector<vector<string>> results;

    // Process each sentence
    for(auto& sent: sentences) {
        auto words = split_words(sent);   // tokenized words
        int n = (int)words.size();

        // Try inserting negation after every word position i
        for(int i = 0; i < n; i++) {
            // If this word is neither not-trigger nor no-trigger, skip it
            if(!is_not_word(words[i]) && !is_no_word(words[i])) {
                continue;
            }

            // Start constructing the output words:
            // copy words up to and including i
            vector<string> out(words.begin(), words.begin() + i + 1);

            // Decide which negation to insert: "no" for is/are, otherwise "not"
            bool no = is_no_word(words[i]);
            out.push_back(no ? "no" : "not");

            // Determine from where to copy the remaining words
            int start = i + 1;

            // If we inserted "no" and the next word is an article, skip it
            start += (no && start < n && is_a_or_the(words[start]));

            // Append the remaining words
            out.insert(out.end(), words.begin() + start, words.end());

            // Save this candidate sentence
            results.push_back(out);
        }
    }

    // Output count
    cout << results.size() << '\n';

    // Output each modified sentence as a single line ending with '.'
    for(auto& r: results) {
        for(int i = 0; i < (int)r.size(); i++) {
            cout << r[i];
            if(i + 1 == (int)r.size()) {
                cout << '.';       // dot at the end of sentence
            } else {
                cout << ' ';       // single spaces between words
            }
        }
        cout << '\n';
    }
}

int main() {
    ios_base::sync_with_stdio(false); // faster I/O
    cin.tie(nullptr);                // avoid flushing cout before every cin

    int T = 1;
    // cin >> T;                     // problem has only one "test": whole statement text
    for(int test = 1; test <= T; test++) {
        read();                      // read entire input into global 'text'
        solve();                     // generate and print all variants
    }

    return 0;
}
```

---

## 4) Python solution (same logic, detailed comments)

```python
import sys

def lower(s: str) -> str:
    """ASCII-lowercase version for case-insensitive comparisons."""
    return s.lower()

def split_words(s: str) -> list[str]:
    """Split sentence into words by whitespace."""
    # Input guarantees single spaces between words, but split() is fine.
    return s.split()

def solve() -> None:
    # Read entire input (may include newlines due to wrapping in files)
    lines = sys.stdin.read().splitlines()

    # Concatenate lines with spaces between them (but avoid double spaces)
    text_parts = []
    for line in lines:
        if not line:
            # Problem statements typically won't contain empty lines,
            # but if they do, treating them as separators is safest.
            continue
        text_parts.append(line)
    text = " ".join(text_parts)

    # Helpers for trigger words (case-insensitive match)
    def is_not_word(w: str) -> bool:
        w = lower(w)
        return w in ("can", "may", "must", "should")

    def is_no_word(w: str) -> bool:
        w = lower(w)
        return w in ("is", "are")

    def is_article(w: str) -> bool:
        w = lower(w)
        return w in ("a", "the")

    # Split into sentences by '.'
    # The dot is not part of words; we will re-add it on output.
    sentences = []
    cur = []
    for ch in text:
        if ch == ".":
            sentences.append("".join(cur))
            cur = []
        else:
            cur.append(ch)

    results: list[list[str]] = []

    # Process each sentence independently, scanning word positions left-to-right
    for sent in sentences:
        words = split_words(sent)
        n = len(words)

        for i in range(n):
            if not (is_not_word(words[i]) or is_no_word(words[i])):
                continue

            out = words[: i + 1]  # copy up to and including i

            if is_no_word(words[i]):
                out.append("no")
                start = i + 1
                # If next word is an article, remove it by skipping
                if start < n and is_article(words[start]):
                    start += 1
                out.extend(words[start:])
            else:
                out.append("not")
                out.extend(words[i + 1 :])

            results.append(out)

    # Print results
    sys.stdout.write(str(len(results)) + "\n")
    for words in results:
        sys.stdout.write(" ".join(words) + ".\n")

if __name__ == "__main__":
    solve()
```

---

## 5) Compressed editorial

Read the whole input as one text string, split it into sentences by `.`. For each sentence, split by spaces into words. For every position `i`, if `words[i]` (case-insensitive) is `can/may/must/should`, output a variant inserting `"not"` after it. If it is `is/are`, output a variant inserting `"no"` after it and, if the next word is `a/the` (case-insensitive), skip that word. Preserve original casing of copied words, print one sentence per line ending with `.`. Output count first. Order is ensured by scanning sentences in order and positions left-to-right.