Random Delivery Attempt Outcome Dataset Generator

Description

Generate synthetic stops with capped retry attempts, explicit first/later success probabilities and integer minor-unit attempt costs; stop attempts after success and delegate first-attempt rate and cost per completed drop. Cost includes failed attempts and failed stops, uses one supplied currency/unit convention, and is undefined when no drops complete; no real-route prediction is implied.

A logistics test dataset combines supplied operating ranges with explicit quantity and unit conventions. Constructed measurements and calculated indicators can exercise reports and calculators without claiming to represent an observed operation or a safe physical plan.

When to use this tool

Use this generator to create reproducible delivery attempt outcome dataset 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 stopCount, maximumAttempts, firstSuccessProbability, laterSuccessProbability, minimumCostMinorUnits, maximumCostMinorUnits, currency, minorUnitsPerUnit 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 stops, summary. Use the conventions below. Keep answer-bearing fields separate when presenting an exercise.

Generate per-stop attempts with separate first and later success probabilities, stopping at success or maximumAttempts. Draw integer costs, sum minor units exactly, convert to the supplied currency unit, and calculate delivery success and cost per completed drop.^[1]

Delegated operations used for this result: first attempt delivery success percent; cost per drop last mile. Their calculation or parsing conventions apply to the corresponding result fields.^{[2, 3]}

Input field	Meaning and units	Accepted input
stopCount	Stop Count	Required. Safe integer; minimum 1; maximum 128.
maximumAttempts	Maximum Attempts	Required. Safe integer; minimum 1; maximum 16.
firstSuccessProbability	First Success Probability	Required. Finite number; minimum 0; maximum 1.
laterSuccessProbability	Later Success Probability	Required. Finite number; minimum 0; maximum 1.
minimumCostMinorUnits	Minimum Cost Minor Units	Required. Safe integer; minimum 0; maximum 9007199254740991.
maximumCostMinorUnits	Maximum Cost Minor Units	Required. Safe integer; minimum 0; maximum 9007199254740991.
currency	Currency	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
minorUnitsPerUnit	Minor Units Per Unit	Required. Safe integer; minimum 1; maximum 9007199254740991.
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
stops	Stops	Required. Array of Object; no unknown keys.; minimum items 1; maximum items 128.
stops[].id	Literal identifier used independently of display labels.	Required. Text.
stops[].attempts	Attempts	Required. Array of Object; no unknown keys.; minimum items 1; maximum items 16.
stops[].attempts[].number	Number	Required. Safe integer; minimum 1; maximum 16.
stops[].attempts[].costMinorUnits	Cost Minor Units	Required. Safe integer; minimum 0; maximum 9007199254740991.
stops[].attempts[].success	Success	Required. Boolean.
stops[].completed	Completed	Required. Boolean.
stops[].firstAttemptSuccess	First Attempt Success	Required. Boolean.
summary	Summary	Required. Object; no unknown keys.
summary.totalStops	Total Stops	Required. Safe integer; minimum 1; maximum 9007199254740991.
summary.completedDrops	Completed Drops	Required. Safe integer; minimum 0; maximum 9007199254740991.
summary.failedDrops	Failed Drops	Required. Safe integer; minimum 0; maximum 9007199254740991.
summary.firstAttemptDeliveries	First Attempt Deliveries	Required. Safe integer; minimum 0; maximum 9007199254740991.
summary.firstAttemptSuccessPercent	First Attempt Success Percent	Required. Finite number; minimum 0; maximum 100.
summary.totalCostMinorUnits	Total Cost Minor Units	Required. Safe integer; minimum 0; maximum 9007199254740991.
summary.totalDeliveryCost	Total Delivery Cost	Required. Finite number; minimum 0.
summary.costPerDrop	Cost Per Drop	Required. Finite number; minimum 0. or Null.
summary.costUndefinedReason	Cost Undefined Reason	Required. Text; exactly "no-completed-drops". or Null.
summary.currency	Currency	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
summary.minorUnitsPerUnit	Minor Units Per Unit	Required. Safe integer; minimum 1; maximum 9007199254740991.
randomness	Replay source and normalized 32-bit seed, or null seed for an advancing context source.	Required. Object; no unknown keys.
randomness.seed	Optional safe-integer 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": {
    "stopCount": 3,
    "maximumAttempts": 3,
    "firstSuccessProbability": 0.5,
    "laterSuccessProbability": 0.8,
    "minimumCostMinorUnits": 100,
    "maximumCostMinorUnits": 300,
    "currency": "synthetic credits",
    "minorUnitsPerUnit": 100,
    "seed": 42
  },
  "output": {
    "stops": [
      {
        "id": "stop-1",
        "attempts": [
          {
            "number": 1,
            "costMinorUnits": 220,
            "success": true
          }
        ],
        "completed": true,
        "firstAttemptSuccess": true
      },
      {
        "id": "stop-2",
        "attempts": [
          {
            "number": 1,
            "costMinorUnits": 271,
            "success": false
          },
          {
            "number": 2,
            "costMinorUnits": 135,
            "success": true
          }
        ],
        "completed": true,
        "firstAttemptSuccess": false
      },
      {
        "id": "stop-3",
        "attempts": [
          {
            "number": 1,
            "costMinorUnits": 154,
            "success": false
          },
          {
            "number": 2,
            "costMinorUnits": 273,
            "success": true
          }
        ],
        "completed": true,
        "firstAttemptSuccess": false
      }
    ],
    "summary": {
      "totalStops": 3,
      "completedDrops": 3,
      "failedDrops": 0,
      "firstAttemptDeliveries": 1,
      "firstAttemptSuccessPercent": 33.33333333333333,
      "totalCostMinorUnits": 1053,
      "totalDeliveryCost": 10.53,
      "costPerDrop": 3.51,
      "costUndefinedReason": null,
      "currency": "synthetic credits",
      "minorUnitsPerUnit": 100
    },
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

A stop can remain failed. Cost per drop is null with an explicit reason when none complete. Currency is a supplied label; no exchange conversion, real delivery forecasting, or accounting verification occurs.
A replay requires the same complete input and implementation. The stated sampling convention applies within its eligible space. A finite draw does not exhaust all possible outputs; repeats remain possible unless a distinct-selection rule is explicit.
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 Delivery Attempt Outcome Dataset Generator — tool.io
Calculation or validation: logistics/first-attempt-delivery-success-percent — tool.io
Calculation or validation: logistics/cost-per-drop-last-mile — tool.io

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