Test fixture
Code transformation while preserving behavior and intent.
The model receives the prompt (and optional system message). The run uses scorer contains_all with the JSON configuration below. Pass/fail and partial credit are determined entirely by that scorer against the model output; no human grading.
Refactor without changing behavior. Return only Python code.
def normalized_email(user):
if "email" in user:
if user["email"]:
return user["email"].strip().lower()
return None
{
"expected_contains": [
"return None",
".strip().lower()"
]
}temperature
0
max_tokens
180
timeout (s)
120
type
scored
file
refactoring_easy_03.json