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Checking AI-Written Code through User-Task Regression Samples

After AI writes the code, how to confirm that the user can proceed from input to save or export? This article organizes normal, empty input, repeated submission, network failure and permission examples with complete tasks, records expected and actual results, and checks the upgraded data and operation status to help small teams extend smooth demonstrations into delivery evidence that can be reviewed.

Chinese edition published 17 Oct 2026 · 阅读中文原文 ↗

Source timingThe public information webpage is verified as of 2026-10-17; please refer to the source for the original date.

Code generation does not mean that the task has been completed

What users need is software that can complete specific tasks. Playwright's official test documents can be used as the technical background for web page function inspection. This article focuses on how to choose test questions and does not provide general passing standards that have not been verified by the project.

Organize samples using operation paths

Start with a complete task, covering entering the page, submitting information, getting results, saving or exporting. Then, empty input, repeated submission, network failure and unauthorized access were added. Each example describes the input, expected results and actual observations. Don't just look at whether an error is reported.

For applications that process customer data, you should check whether different users are isolated from each other, how they are displayed after deletion, and whether half-completed records are left when they fail. After the version is updated, review the affected tasks first; retain the recoverable version if necessary to avoid a functional adjustment that will make existing customers unable to continue using it.

Record demonstration and verification separately

You can choose a smooth path for demonstration, but you need to actively look for failure situations for verification. Deliver inspection results and known issues so customers know what is covered by the pilot. Extended reading: Research on the Prototype of Stars in the Cloud.

Sources and editorial notes

Web page data verification: 2026-10-17. AI-assisted data compilation and writing, ChinaOPC independent organization for expression and analysis, off-site interviews or original text reprinting. The work steps and acceptance samples are recommended by ChinaOPC. They need to be tried with approved materials and do not pretend to be delivered to a verified customer. Tool functions, deployment conditions and data processing rules are subject to the current official documents. English translation of the Chinese edition, prepared with machine assistance and editorial checks. Source verification dates refer to the original Chinese research.

Source titles and publisher names are retained in their original language. Refer to the linked originals for official documents and current requirements.

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