AI-Code Control Coverage

Audit human-review controls for AI-generated code.

Description

Human review of AI-generated code needs specified control evidence.

Human review of AI-generated code needs specified control evidence. Coverage of labels differs from verifying code or review quality.^[1]

Audit human-review controls for AI-generated code.

When to use AI-Code Control Coverage

Use this tool to audit human-review controls for AI-generated code.

Prepare the documented facts, aligned totals or expected/observed evidence labels requested. Choose applicable requirements and thresholds separately before interpreting a planning screen.

How to use AI-Code Control Coverage and understand its results

Prepare the documented facts, aligned totals or expected/observed evidence labels requested. Choose applicable requirements and thresholds separately before interpreting a planning screen.
Enter requiredControls, documentedControls using the field table and calculation rules, then run the tool.
Read coveragePercent, matched, missing, unexpected. The explanation below defines the units, signs, ordering and any flags or placeholder values.
If the tool reports an input issue, correct the values and run it again. Apply the stated assumptions when interpreting a successfully returned result.

Input field	Meaning	Value type; see rules below	Requirement
requiredControls	Required AI-code controls	list of string	Required
documentedControls	Documented controls	list of string	Required

Enter requiredControls as the nonempty expected list and documentedControls as observations, which may be empty. Trim entries, compare case-insensitively using en-US lowercase and collapse duplicates. Return matched/missing expected labels and unexpected observed labels. Output follows first occurrence order with the last duplicate’s trimmed spelling.

coverage%=100matchedUnique/expectedUnique

Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.

Output field	Meaning	Value type
coveragePercent	Coverage (%)	number; minimum: 0; maximum: 100
matched	Matched items	list of string
missing	Missing items	list of string
unexpected	Unexpected items	list of string

json

{
  "input": {
    "requiredControls": [
      "alpha",
      "beta",
      "gamma",
      "delta"
    ],
    "documentedControls": [
      "beta",
      "alpha",
      "extra"
    ]
  },
  "output": {
    "coveragePercent": 50,
    "matched": [
      "alpha",
      "beta"
    ],
    "missing": [
      "gamma",
      "delta"
    ],
    "unexpected": [
      "extra"
    ]
  }
}

Limitations and assumptions

No code is analyzed or human review tested. Blank entries are errors; requirements are entirely caller-supplied and items have equal weight.

Numeric inputs, where present, must be finite. Follow the calculation-specific rules for overflow, underflow and exceptional cases. Lists are limited to 100,000 entries; the rules above may require smaller limits. Missing required fields, extra fields, wrong value types and violations of the calculation rules are input errors.

Alternative or Complementary methods

Use Cloud Responsibility Coverage: Audit cloud shared-responsibility assignments. For a complementary task, use PAM Evidence Coverage: Audit privileged-access-management evidence.

References

AI-Code Control Coverage — tool.io

Similar or alternative tools

Cloud Responsibility Coverage
Audit cloud shared-responsibility assignments.
PAM Evidence Coverage
Audit privileged-access-management evidence.