Random Kakuro Run Completion Exercise Generator

Description

Generate a distinct-digit Kakuro run with hidden cells and all feasible unordered remaining digit sets, without assuming ordered uniqueness.

A generated practice exercise contains a prompt and an answer key under a specific rule set. A planted answer establishes one possible solution; only an explicit enumeration or uniqueness check establishes whether alternatives exist.

Generate a distinct-digit Kakuro run with hidden cells and all feasible unordered remaining digit sets, without assuming ordered uniqueness.

When to use this tool

Use this generator to create reproducible kakuro run completion exercise cases from the supplied model or bank. Inspect the returned evidence before using cases in a test or exercise.

How to use the tool and how it works

Supply length, hiddenCount in the field shapes below. Set seed when you need an explicit replay.
Run the tool and correct any input error. For generated controls, distinguish a successful fixture containing an invalid case from failure to generate the fixture.
Read puzzle, answer. Use the conventions below and keep answer-bearing fields separate when presenting an exercise.

Draw distinct digits one through nine, calculate their sum, and hide selected cells as zero. Enumerate unordered missing-digit sets satisfying the visible digits and target, cross-check their count, and multiply by hiddenCount factorial for ordered completions.^[1]

Delegated operations used for this result: kakuro row sum distinct digits checker. Their calculation or parsing conventions apply to the corresponding result fields.^[2]

Input field	Meaning and units	Accepted input
length	Length	Required. Safe integer; minimum 1; maximum 9.
hiddenCount	Hidden Count	Required. Safe integer; minimum 0; maximum 9.
seed	Optional numeric seed; takes precedence over context randomness. Without either, use the fixed tool.io default seed.	Optional. Safe integer.

Output field	Interpretation	Returned shape
puzzle	Puzzle	Required. Object; no unknown keys.
puzzle.targetSum	Target Sum	Required. Safe integer.
puzzle.cells	Cells	Required. Array of Safe integer; minimum 0; maximum 9.; minimum items 0; maximum items 9.
answer	Answer	Required. Object; no unknown keys.
answer.solution	Solution	Required. Array of Safe integer; minimum 0; maximum 9.; minimum items 0; maximum items 9.
answer.remainingDigitSets	Remaining Digit Sets	Required. Array of Array of Safe integer; minimum 0; maximum 9.; minimum items 0; maximum items 9.; minimum items 0; maximum items 512.
answer.unorderedSetCount	Unordered Set Count	Required. Safe integer.
answer.orderedCompletionCount	Ordered Completion Count	Required. Safe integer.
randomness	Replay metadata: source is seed or context; seed is the normalized 32-bit seed or null for a context source.	Required. Object; no unknown keys.
randomness.seed	Optional numeric replay seed; normalization and precedence are explained below.	Required. Safe integer. or Null.
randomness.source	Source	Required. Text; one of "context", "seed".

An explicit safe-integer seed takes precedence over injected context randomness and is normalized to an unsigned 32-bit integer. With no seed and no context source, replay uses the fixed tool.io default seed. A context source must return finite values from zero inclusive to one exclusive; its advancing state must be retained separately. randomness records the source and normalized seed, or null for context. These generators are not cryptographic random sources.

json

{
  "input": {
    "length": 3,
    "hiddenCount": 2,
    "seed": 42
  },
  "output": {
    "puzzle": {
      "targetSum": 19,
      "cells": [
        0,
        4,
        0
      ]
    },
    "answer": {
      "solution": [
        6,
        4,
        9
      ],
      "remainingDigitSets": [
        [
          6,
          9
        ],
        [
          7,
          8
        ]
      ],
      "unorderedSetCount": 2,
      "orderedCompletionCount": 4
    },
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

The planted run need not be uniquely completable. This is one Kakuro run rather than an intersecting grid; zero means unknown and is never a solution digit.
A replay requires the same complete input and implementation. Randomized construction does not guarantee uniform coverage of every feasible output; finite samples can repeat unless a distinct-selection rule is explicitly stated.
The field tables state structural bounds; cross-field constraints and bounded search or output budgets also apply. Unknown keys are rejected where the object contract disallows them. Input errors are distinct from null fields and deliberate invalid controls in a successful output.

Alternative or Complementary methods

For a supplied example, inspect the returned construction or delegated check directly. To evaluate a consumer, also test cases chosen for its own boundaries; a generated finite corpus does not establish exhaustive coverage.

References

Tool behavior and example: Random Kakuro Run Completion Exercise Generator — tool.io
Calculation or validation: game/kakuro-row-sum-distinct-digits-checker — tool.io

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