Kenton Labs / Programs & systems

Abstract interpretation

Use interval summaries to enclose concrete values, and distinguish containment from exact sets.

The vocabulary.

These definitions state the objects and properties used by the dataset. The complete instance specification remains the authority for each result.

Concrete state set
The actual values attainable from the declared input domain.
Interval abstraction
A lower and upper bound enclosing concrete values.
Sound transfer
An abstract operation that contains every concrete output.

How the dataset works.

Three deterministic instances define this family. Each includes its input model, a checked result, evidence, and an acceptance procedure. Download the complete dataset JSON ↘ or the area’s readable source ↘.

Acceptance procedure

  1. Start from every integer in the initial interval.
  2. Apply each affine transform to the concrete set.
  3. Apply endpoint arithmetic to the interval, reordering endpoints for negative scales.
  4. Check every concrete value remains enclosed and the final bounds are tight.

Cost and scope

With a concrete interval of k integers and t transformations, this finite replay costs O(kt). Abstract endpoint propagation alone costs O(t).

A common failure

A tight interval can include unattainable interior values; it is not necessarily an exact concrete set.

Worked records.

Three instances expose concrete claims and the artifacts that establish or refute them. Expand a record for the problem, checker reasoning, formal payload, and verification metadata.

A positive affine transferComplete concrete inputs + interval transfer replay

The problem

Compute sound interval bounds for a sequence of mathematical-integer affine transforms.

The checked result

Sound enclosure: yes; Tight interval bounds: yes.

Endpoint propagation encloses every concrete output. Negative multiplication swaps extrema; multiple transformations compose while preserving containment.

Why the checker accepts it

  1. Start from every integer in the initial interval.
  2. Apply each affine transform to the concrete set.
  3. Apply endpoint arithmetic to the interval, reordering endpoints for negative scales.
  4. Check every concrete value remains enclosed and the final bounds are tight.

Formal specification

{
  "initial_interval": [
    -2,
    3
  ],
  "transforms": [
    [
      2,
      1
    ]
  ]
}

Claim and evidence

{
  "claim": {
    "sound": true,
    "tight_interval": true
  },
  "witness": {
    "intervals": [
      [
        -2,
        3
      ],
      [
        -3,
        7
      ]
    ]
  }
}

Dataset construction

Deterministic finite fixture; full enumeration or witness replay as stated. Structured JSON; field meanings are stated in the specification. Acceptance covers 6 checker units for this record; the unit type is stated in its verification scope.

Complexity and limits

With a concrete interval of k integers and t transformations, this finite replay costs O(kt). Abstract endpoint propagation alone costs O(t).

The abstraction encloses gaps. Machine overflow, branches, and widening are not modeled.

A boundary to investigate

A tight interval can include unattainable interior values; it is not necessarily an exact concrete set. Add control-flow joins, fixed points, widening, and overflow-specific abstractions.

Readable source ↘Record JSON ↘Full area ↗Related KL-FCS-038 ↘Related KL-FCS-039 ↘
Negative scaling reverses boundsComplete concrete inputs + interval transfer replay

The problem

Compute sound interval bounds for a sequence of mathematical-integer affine transforms.

The checked result

Sound enclosure: yes; Tight interval bounds: yes.

Endpoint propagation encloses every concrete output. Negative multiplication swaps extrema; multiple transformations compose while preserving containment.

Why the checker accepts it

  1. Start from every integer in the initial interval.
  2. Apply each affine transform to the concrete set.
  3. Apply endpoint arithmetic to the interval, reordering endpoints for negative scales.
  4. Check every concrete value remains enclosed and the final bounds are tight.

Formal specification

{
  "initial_interval": [
    -3,
    4
  ],
  "transforms": [
    [
      -2,
      3
    ]
  ]
}

Claim and evidence

{
  "claim": {
    "sound": true,
    "tight_interval": true
  },
  "witness": {
    "intervals": [
      [
        -3,
        4
      ],
      [
        -5,
        9
      ]
    ]
  }
}

Dataset construction

Deterministic finite fixture; full enumeration or witness replay as stated. Structured JSON; field meanings are stated in the specification. Acceptance covers 8 checker units for this record; the unit type is stated in its verification scope.

Complexity and limits

With a concrete interval of k integers and t transformations, this finite replay costs O(kt). Abstract endpoint propagation alone costs O(t).

The abstraction encloses gaps. Machine overflow, branches, and widening are not modeled.

A boundary to investigate

A tight interval can include unattainable interior values; it is not necessarily an exact concrete set. Add control-flow joins, fixed points, widening, and overflow-specific abstractions.

Readable source ↘Record JSON ↘Full area ↗Related KL-FCS-037 ↘Related KL-FCS-039 ↘
Compose three abstract transfersComplete concrete inputs + interval transfer replay

The problem

Compute sound interval bounds for a sequence of mathematical-integer affine transforms.

The checked result

Sound enclosure: yes; Tight interval bounds: yes.

Endpoint propagation encloses every concrete output. Negative multiplication swaps extrema; multiple transformations compose while preserving containment.

Why the checker accepts it

  1. Start from every integer in the initial interval.
  2. Apply each affine transform to the concrete set.
  3. Apply endpoint arithmetic to the interval, reordering endpoints for negative scales.
  4. Check every concrete value remains enclosed and the final bounds are tight.

Formal specification

{
  "initial_interval": [
    0,
    4
  ],
  "transforms": [
    [
      2,
      1
    ],
    [
      -1,
      5
    ],
    [
      3,
      -2
    ]
  ]
}

Claim and evidence

{
  "claim": {
    "sound": true,
    "tight_interval": true
  },
  "witness": {
    "intervals": [
      [
        0,
        4
      ],
      [
        1,
        9
      ],
      [
        -4,
        4
      ],
      [
        -14,
        10
      ]
    ]
  }
}

Dataset construction

Deterministic finite fixture; full enumeration or witness replay as stated. Structured JSON; field meanings are stated in the specification. Acceptance covers 5 checker units for this record; the unit type is stated in its verification scope.

Complexity and limits

With a concrete interval of k integers and t transformations, this finite replay costs O(kt). Abstract endpoint propagation alone costs O(t).

The abstraction encloses gaps. Machine overflow, branches, and widening are not modeled.

A boundary to investigate

A tight interval can include unattainable interior values; it is not necessarily an exact concrete set. Add control-flow joins, fixed points, widening, and overflow-specific abstractions.

Readable source ↘Record JSON ↘Full area ↗Related KL-FCS-037 ↘Related KL-FCS-038 ↘

Go further.

Add control-flow joins, fixed points, widening, and overflow-specific abstractions.

Questions to investigate

  1. A tight interval can include unattainable interior values; it is not necessarily an exact concrete set.
  2. Which assumption in the specification can be changed to make the current evidence insufficient?
  3. Add control-flow joins, fixed points, widening, and overflow-specific abstractions.

Conceptual references

These sources explain the surrounding theory. The linked material was not imported as a dataset, and these records do not claim checking by the source’s software.

Related areas