AI Test Case Optimizer

AI Test Optimization

Paste test cases (any format) and receive an optimised version with change notes — merged redundant steps, explicit data, atomic assertions and consistent naming.

Privacy: Requires a free Mutqan account. Your input is sent to the Mutqan AI service to generate the result; prompts and results are not stored — only your account's usage counts for the daily allowance. How the AI tools work

What is a test case?

A test case is a specified set of preconditions, inputs, actions and expected results written to verify one requirement or behaviour (ISTQB). A test scenario is broader — a user goal such as "checkout with an expired card" — that several test cases cover. Good cases are unambiguous, repeatable by someone else, traceable to a requirement, and include the negative and boundary paths, not only the happy one.

Read the guide: How to Write Test Cases

How to use AI Test Case Optimizer

  1. Paste your existing test cases in any format — a table, a numbered list, Gherkin or prose.
  2. Optionally add context: the feature, your naming conventions, your priority rules.
  3. Pick the output language and press Improve.
  4. Compare the quality score before and after, review every change and its reason in the change log, then download the optimised cases as CSV, Markdown or JSON.

AI Test Case Optimizer features

  • Parses any format (tables, lists, Gherkin, prose) into structured cases
  • Atomic steps, explicit data, complete preconditions, observable expected results
  • Splits compound cases and merges duplicates without losing coverage
  • Change log with reasons and before/after quality scores

AI Test Case Optimizer example

Before → after

Input:

1. Delete lookup value - delete works

Output:

TC-001 Admin deletes an unreferenced lookup value — steps 1–2, expected: success toast, value removed from list and API

Frequently asked questions about AI Test Case Optimizer

Will it change what my tests verify?

No. Coverage is preserved; only clarity, structure and precision improve. Merges and splits are listed in the change log so you can review them.

What happens to duplicate or compound cases?

Duplicates are merged and compound cases are split into single-purpose ones, and each merge or split is recorded in the change log — no scenario is dropped silently.

What do the quality scores measure?

The tool rates your original cases and the optimised ones from 0 to 100 on what it improves — precise titles, atomic steps, explicit data, complete preconditions and observable expected results — so you can see how much the rewrite gained.

Technical notes

The result is the optimised suite — up to 40 cases, each with preconditions, test data, steps, an observable expected result, a priority and a risk — a change log that names the case, the change and the reason for each edit, and quality scores from 0 to 100 before and after. Existing IDs are kept; cases without IDs are numbered TC-001, TC-002 … in their original order.

References