Editing AI for Code Generation (section)

== <span style="color: #FFFFFF;">Applying</span> ==
'''Code generation with the OpenAI API:'''

<syntaxhighlight lang="python">
from openai import OpenAI

client = OpenAI()

def generate_and_test(spec: str, test_cases: list[dict]) -> dict:
    """Generate code from spec, test it, and return results."""

    # Step 1: Generate code
    response = client.chat.completions.create(
        model="gpt-4o",
        messages=[
            {"role": "system", "content": "You are an expert Python programmer. "
             "Write clean, well-documented, production-quality code. "
             "Include only the function implementation, no explanation."},
            {"role": "user", "content": f"Implement the following:\n\n{spec}"}
        ],
        temperature=0.2  # Low temperature for deterministic code
    )
    code = response.choices[0].message.content

    # Step 2: Execute and test (in a sandbox!)
    results = []
    exec_globals = {}
    exec(code, exec_globals)  # In production: use subprocess or sandbox

    for test in test_cases:
        func_name = test['function']
        args = test['args']
        expected = test['expected']
        actual = exec_globals[func_name](*args)
        results.append({
            'passed': actual == expected,
            'expected': expected,
            'actual': actual
        })

    return {'code': code, 'results': results,
            'pass_rate': sum(r['passed'] for r in results) / len(results)}

# Example usage
spec = """
Function: merge_intervals(intervals)
Given a list of intervals [start, end], merge all overlapping intervals
and return the list of merged intervals sorted by start.
Example: [[1,3],[2,6],[8,10],[15,18]] → [[1,6],[8,10],[15,18]]
"""
test_cases = [
    {'function': 'merge_intervals', 'args': [[[1,3],[2,6],[8,10],[15,18]]], 'expected': [[1,6],[8,10],[15,18]]},
    {'function': 'merge_intervals', 'args': [[[1,4],[4,5]]], 'expected': [[1,5]]},
]
result = generate_and_test(spec, test_cases)
print(f"Pass rate: {result['pass_rate']*100:.0f}%")
</syntaxhighlight>

; Code generation use case map
: '''IDE integration''' → GitHub Copilot, Cursor, Continue.dev (VS Code extension)
: '''Chat-based coding''' → Claude, GPT-4o, Gemini in chat with code interpreter
: '''Autonomous agents''' → Devin, SWE-agent, OpenHands (multi-step task completion)
: '''Code review''' → AI-powered PR review bots (GitHub Copilot PR review, CodeRabbit)
: '''Security scanning''' → Semgrep + AI, Snyk Code, GitHub Advanced Security
: '''Documentation''' → AI docstring generation, README writing, API doc generation
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