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To generate a puzzle with exactly one solution, first create a valid candidate, then run a solver that counts solutions. Keep the candidate only when the count is exactly one. For a daily puzzle that is identical for everyone, seed a deterministic pseudorandom number generator from a canonical date and keep the seed format, generator, and generation procedure stable.

What “exactly one solution” means

A puzzle generator and a puzzle solver have different jobs. The generator constructs a candidate puzzle; the solver checks it against the puzzle’s rules. A solution counter should distinguish three outcomes:

  • Zero solutions: the clues conflict or the puzzle is otherwise invalid.
  • One solution: the puzzle is unique.
  • Two or more solutions: the puzzle is ambiguous.

For uniqueness, the solver does not need to count every possible solution. Stop as soon as it finds a second one. That makes the test useful even when an ambiguous puzzle has many completions.

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Uniqueness does not establish difficulty. A puzzle can have one solution and still require guessing or advanced solving techniques. If you promise that a puzzle is solvable by logic alone, test it with the specific logic-only solver or technique set that your promise names.

Make repeatable puzzles with an explicit seed

Math.random() is unsuitable when a user must choose or replay a seed: its initial seed is selected by the JavaScript implementation and cannot be set or reset by the user. It is also not cryptographically secure. MDN’s documentation describes those limitations. Crypto.getRandomValues() supplies cryptographically strong random values, but it is not a substitute for a deterministic, shared seed; the underlying pseudorandom algorithm can vary by user agent.

For repeatable puzzle generation, use a seeded PRNG. MDN’s glossary explains that a PRNG returns the same sequence when given the same starting parameters or seed. That alone is not enough for stable daily puzzles: the seed normalization, PRNG algorithm, generation order, and number and order of random draws must also remain unchanged.

A small seeded PRNG

This example hashes a text seed and feeds it to a compact deterministic generator. It is suitable for reproducible puzzle generation, not for security-sensitive randomness.

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function makeRng(seedText) {
  let hash = 2166136261;
  for (let i = 0; i < seedText.length; i++) {
    hash ^= seedText.charCodeAt(i);
    hash = Math.imul(hash, 16777619);
  }
  let state = hash >>> 0;

  return function random() {
    state = (state + 0x6D2B79F5) | 0;
    let value = state;
    value = Math.imul(value ^ (value >>> 15), value | 1);
    value ^= value + Math.imul(value ^ (value >>> 7), value | 61);
    return ((value ^ (value >>> 14)) >>> 0) / 4294967296;
  };
}

function shuffle(items, random) {
  for (let i = items.length - 1; i > 0; i--) {
    const j = Math.floor(random() * (i + 1));
    [items[i], items[j]] = [items[j], items[i]];
  }
  return items;
}

Define the daily seed contract

Choose one canonical date and puzzle identity, for example a UTC date formatted as YYYY-MM-DD, a puzzle type, and a generator version. The exact format is an engineering choice; make it explicit so every client uses the same input.

const seed = `${utcDate}|sudoku|generator-v1`;
const random = makeRng(seed);

Do not derive the date from each visitor’s local clock if the puzzle must match worldwide: a local midnight can correspond to different UTC dates. Define the timezone boundary, and retain old generator versions if players must be able to replay historical daily puzzles after you change the algorithm.

Generate a Sudoku and prove its uniqueness

A completed valid Sudoku grid is only the starting solution, not the playable puzzle. Build a complete grid, remove clues one at a time, and keep each removal only if a solution counter still finds exactly one completion.

1. Fill a complete grid

The following code uses backtracking. At each step it selects an empty cell with the fewest legal values, then tries those values in seeded-random order. This “fewest candidates first” choice is a search heuristic, not a requirement of Sudoku.

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function candidates(board, row, col) {
  const used = new Set();
  for (let i = 0; i < 9; i++) {
    used.add(board[row][i]);
    used.add(board[i][col]);
  }
  const boxRow = Math.floor(row / 3) * 3;
  const boxCol = Math.floor(col / 3) * 3;
  for (let r = boxRow; r < boxRow + 3; r++) {
    for (let c = boxCol; c < boxCol + 3; c++) used.add(board[r][c]);
  }
  const result = [];
  for (let n = 1; n <= 9; n++) if (!used.has(n)) result.push(n);
  return result;
}

function fillGrid(board, random) {
  let best = null;
  let bestOptions = null;

  for (let r = 0; r < 9; r++) {
    for (let c = 0; c < 9; c++) {
      if (board[r][c] !== 0) continue;
      const options = candidates(board, r, c);
      if (options.length === 0) return false;
      if (bestOptions === null || options.length < bestOptions.length) {
        best = [r, c];
        bestOptions = options;
        if (options.length === 1) break;
      }
    }
    if (bestOptions?.length === 1) break;
  }

  if (best === null) return true;
  const [row, col] = best;
  for (const value of shuffle(bestOptions, random)) {
    board[row][col] = value;
    if (fillGrid(board, random)) return true;
  }
  board[row][col] = 0;
  return false;
}

The board uses 0 for an empty cell. Start with a 9-by-9 array of zeroes. A successful call leaves a complete grid in that array; copy it before removing clues so you retain the solution.

2. Count solutions, stopping at two

This counter mutates the supplied board while searching and restores each trial cell afterward. It returns 0, 1, or 2, where 2 means “at least two.”

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function countSudokuSolutions(board, limit = 2) {
  let best = null;
  let bestOptions = null;

  for (let r = 0; r < 9; r++) {
    for (let c = 0; c < 9; c++) {
      if (board[r][c] !== 0) continue;
      const options = candidates(board, r, c);
      if (options.length === 0) return 0;
      if (bestOptions === null || options.length < bestOptions.length) {
        best = [r, c];
        bestOptions = options;
        if (options.length === 1) break;
      }
    }
    if (bestOptions?.length === 1) break;
  }

  if (best === null) return 1;
  const [row, col] = best;
  let count = 0;
  for (const value of bestOptions) {
    board[row][col] = value;
    count += countSudokuSolutions(board, limit - count);
    board[row][col] = 0;
    if (count >= limit) return limit;
  }
  return count;
}

3. Remove clues while preserving uniqueness

Try cells in seeded-random order. Restore a clue whenever removing it makes the puzzle unsolvable or ambiguous.

function generateSudoku(random) {
  const solution = Array.from({ length: 9 }, () => Array(9).fill(0));
  if (!fillGrid(solution, random)) throw new Error("Could not fill Sudoku grid");

  const puzzle = solution.map(row => row.slice());
  const cells = shuffle(
    Array.from({ length: 81 }, (_, index) => index),
    random
  );

  for (const index of cells) {
    const row = Math.floor(index / 9);
    const col = index % 9;
    const saved = puzzle[row][col];
    puzzle[row][col] = 0;
    if (countSudokuSolutions(puzzle, 2) !== 1) puzzle[row][col] = saved;
  }

  return { puzzle, solution };
}

This procedure guarantees uniqueness for each accepted removal because it checks the candidate puzzle, but it does not guarantee a particular clue count, symmetry, or difficulty. Those are separate generation requirements. Clue count alone is not a reliable difficulty label; if you publish difficulty ratings, define the grading method, such as the techniques a specified solver needs or a measured solver complexity.

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Generate and validate a Nonogram

A Nonogram is defined by run-length clues for every row and column. A run is a consecutive sequence of filled cells; runs are listed in order, and distinct runs must have at least one empty cell between them. A fully blank line needs a consistent representation, such as an empty clue array.

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Derive clues from a candidate picture

Represent the picture as a rectangular array of booleans, where true means filled. Derive row and column clues from the same candidate so the two clue sets describe one known solution.

function lineClue(line) {
  const clues = [];
  let run = 0;
  for (const filled of line) {
    if (filled) run++;
    else if (run > 0) {
      clues.push(run);
      run = 0;
    }
  }
  if (run > 0) clues.push(run);
  return clues;
}

function cluesFromPicture(picture) {
  const height = picture.length;
  const width = picture[0].length;
  const rows = picture.map(lineClue);
  const columns = Array.from({ length: width }, (_, c) =>
    lineClue(picture.map(row => row[c]))
  );
  return { rows, columns, width, height };
}

Enumerate legal line patterns

For a line of a known length, generate every binary pattern that matches its clues. This makes the constraint explicit: every possible row or column must be one of its clue-compatible patterns.

function linePatterns(length, clues) {
  if (clues.length === 0) return [Array(length).fill(false)];
  const patterns = [];
  const pattern = Array(length).fill(false);

  function place(runIndex, earliestStart) {
    if (runIndex === clues.length) {
      patterns.push(pattern.slice());
      return;
    }
    const remainingRuns = clues
      .slice(runIndex)
      .reduce((sum, value) => sum + value, 0);
    const separators = clues.length - runIndex - 1;
    const latestStart = length - remainingRuns - separators;
    const runLength = clues[runIndex];

    for (let start = earliestStart; start <= latestStart; start++) {
      for (let i = start; i < start + runLength; i++) pattern[i] = true;
      place(runIndex + 1, start + runLength + 1);
      for (let i = start; i < start + runLength; i++) pattern[i] = false;
    }
  }

  place(0, 0);
  return patterns;
}

Count Nonogram solutions

The solver below assigns rows recursively. After each row, it rejects a branch if any column’s partial cells cannot match any legal pattern for that column. It stops after two complete grids. This is a practical implementation approach; the available source material does not establish a universal reference algorithm or performance guarantee.

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function countNonogramSolutions(rowClues, columnClues, width, height, limit = 2) {
  if (rowClues.length !== height || columnClues.length !== width) {
    throw new Error("Clue dimensions do not match the grid");
  }
  const rowOptions = rowClues.map(clue => linePatterns(width, clue));
  const columnOptions = columnClues.map(clue => linePatterns(height, clue));
  if (rowOptions.some(options => options.length === 0) ||
      columnOptions.some(options => options.length === 0)) return 0;

  const chosenRows = [];
  let solutions = 0;

  function columnsStillPossible(candidateRow) {
    for (let c = 0; c < width; c++) {
      const possible = columnOptions[c].some(pattern => {
        for (let r = 0; r < chosenRows.length; r++) {
          if (pattern[r] !== chosenRows[r][c]) return false;
        }
        return pattern[chosenRows.length] === candidateRow[c];
      });
      if (!possible) return false;
    }
    return true;
  }

  function search(rowIndex) {
    if (solutions >= limit) return;
    if (rowIndex === height) {
      solutions++;
      return;
    }
    for (const row of rowOptions[rowIndex]) {
      if (!columnsStillPossible(row)) continue;
      chosenRows.push(row);
      search(rowIndex + 1);
      chosenRows.pop();
      if (solutions >= limit) return;
    }
  }

  search(0);
  return solutions;
}

For a generated picture, derive its clues with cluesFromPicture(picture), then call countNonogramSolutions(rows, columns, width, height, 2). Keep the clues only if the result is 1. The row-pattern enumeration can grow quickly for long lines, and the recursive search may explore many combinations; larger puzzles may need stronger propagation, candidate caching, or more selective branching.

Keep generation claims precise

Before publishing a puzzle, decide what you are guaranteeing and verify that property with the appropriate method:

  • “Has exactly one solution” requires a solver that counts completions and distinguishes one from two or more.
  • “Solvable without guessing” requires the intended logic-only solving method to finish it; uniqueness by itself does not prove that.
  • “Daily puzzle is the same for everyone” requires a shared date and timezone rule, seed format, PRNG, and deterministic generation procedure.
  • “Easy,” “medium,” or “hard” requires a stated grading method; neither uniqueness nor clue count supplies a universal difficulty rating.

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