3 papers
cs.SE2026
Unreliable in Practice? A Comprehensive Study of Errors in LLM-Generated Code
Rodrigo Pato Nogueira, Marco Vieira, João R. Campos
Large Language Models (LLMs) are being widely used for coding, with reports indicating that AI now generates an increasing share of production code. Studies show that LLMs can sign…
cs.SE2026
PROBE: Benchmarking Code Generation in Large Language Models
Rodrigo Pato Nogueira, Marco Vieira, João R. Campos
Large Language Models (LLMs) are increasingly being used in everyday software engineering tasks, particularly in automated code generation. Despite their widespread adoption, these…
cs.SE2026
A Systematic Methodology for Evaluating Failure Independence in LLM-Generated Code
Rodrigo Pato Nogueira, Karthik Pattabiraman, Marco Vieira +1
N-Version Programming (NVP) improves software reliability by executing multiple independent implementations and combining outputs, but its adoption is limited by high cost and the…