AI0-001 Implementing AI Solutions Practice Question
A company is deploying a code generation AI assistant for internal developers. They want to ensure the assistant does not generate code with security vulnerabilities. Which testing approach is MOST critical?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Integration tests that send security-focused prompts and validate the generated code against a static analysis tool
Integration tests that call the model with security-related prompts and scan outputs for vulnerabilities directly assess this requirement. Unit tests on data pipelines are for data correctness, not security of generated code.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Unit tests for the data pipeline that preprocesses prompts
Why it's wrong here
Unit tests ensure data pipeline correctness but do not test generated code for vulnerabilities.
- ✗
Evaluation framework that measures BLEU score on a held-out set of code samples
Why it's wrong here
BLEU measures syntactic similarity, not security; it does not detect vulnerabilities.
- ✗
Regression tests that compare outputs of new model versions against a golden dataset
Why it's wrong here
Regression tests catch functional regressions but not security vulnerabilities unless specifically designed.
- ✓
Integration tests that send security-focused prompts and validate the generated code against a static analysis tool
Why this is correct
Integration tests with security scanning directly validate that the model avoids generating vulnerable code.
About these practice questions
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI0-001 practice question is part of Courseiva's free CompTIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI0-001 exam.