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ML for QA automation
·
Module 6
Deep Learning: LLMs for Code Generation & Analysis
1
Prompting Techniques for Large Language Models
Describe zero-shot, one-shot, and few-shot prompting techniques for large language models.
Generating Unit Tests with LLMs
Call an LLM API to generate unit tests from function signatures and docstrings.
3
Crafting Prompts for Structured Test Cases
Design effective prompts that produce structured, executable test case output.
4
Grounding LLMs with RAG in Codebases
Apply retrieval-augmented generation (RAG) to ground LLM output in the specific context of a codebase.
Few-Shot Prompting for Code Smells & Test Flakiness
Use few-shot prompting to identify a specific code smell or hypothesize a source of test flakiness.
6
Measuring LLM Test Coverage
Evaluate LLM-generated tests by executing them and measuring their code coverage.
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Deep Learning: Code as Data with Embeddings
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Project Definition and Scoping