What Is Structured Output? Explained For Software Testers | AI Tester Dictionary #026
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What Is Structured Output? Explained For Software Testers | AI Tester Dictionary #026
106 просмотров · 3 дня назад
Software Testing Trends
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106 просмотров · 3 дня назад
A test has failed, and you ask an AI assistant to analyse it. The assistant writes you a paragraph saying the issue is high severity, that it is in the document processing component, and that you should check the validation logic. That is a useful answer for a person. But a script that files defects in your tracker needs a separate severity field and a separate component field, and it cannot find either one inside a sentence.
Structured output means the model returns its answer in a fixed shape that you define in advance. You describe that shape in a schema, which lists the fields the answer must have, the type of each field, and the values each field may take. The wording inside a field can change from one answer to the next, but the fields stay the same, and that is what lets software rely on the answer.
A common mistake is to assume that valid JSON means a correct answer. A payload that says the severity is low can parse without errors and follow every rule in the schema, even when the test run it describes deleted every record in the database. To catch this, keep a set of logs where you already know the right severity, and compare the model's answers with them.
The episode also shows where the schema validator sits in a real system and how to test that it stops a bad answer, why JSON is only one of the formats structured output can use, the six checks to run on every structured answer, and what the model should do when it cannot tell the answer.
⏱️ Chapters
0:00 A paragraph, and what software makes of it
0:33 What the AI Tester Dictionary is
0:44 A shape you decided in advance
1:11 Same analysis, different reader
1:31 Where the answer goes next
2:01 Three lines of log, one payload
2:45 JSON is one format
3:13 Six checks on every answer
3:49 What should it say when it cannot tell?
4:19 Valid is not correct
4:49 What to hold on to
🔑 Key takeaways
• Structured output is an answer shaped by a schema you define in advance, so software can use it without guessing
• It adds a validation step to your system, and that step is where a bad answer should be stopped, so test it by sending an answer with a missing field
• There are six checks to run on every structured answer: it parses, every required field is present, each field has the right type, each value is allowed, there are no extra fields, and the values are true. A validator can run the first five; the sixth needs a person who knows the right answer
• Let the schema say unknown, or the model will fill in a required field even when the log does not support it
• A valid answer is not always a correct one. A severity of low can pass every schema rule while describing a failure that deleted every record, so check the meaning separately from the shape
📚 In this series
#001 — Artificial Intelligence
#002 — Machine Learning
#003 — Deep Learning
#004 — Generative AI
#005 — Large Language Models
#006 — Transformer
#007 — Diffusion Model
#008 — Foundation Model
#009 — Token
#010 — Context Window
#011 — Prompt
#012 — System Prompt
#013 — Prompt Engineering
#014 — Temperature
#015 — Top K and Top P
#016 — Hallucination
#017 — Embeddings
#018 — Vector Database
#019 — Semantic Search
#020 — Retrieval-Augmented Generation
#021 — Chunking
#022 — Reranking
#023 — Knowledge Graph
#024 — Multimodal AI
#025 — Function Calling
#026 — Structured Output ← you are here
#027 — Grounding
▶️ Previously
#025 — Function Calling: a model asking for a named function with arguments, and the boundary your application defends.
• What Is Function Calling? Explained For So...
▶️ Next in the series
#027 — Grounding: tying what a model says to something real.
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