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cs.SE2026
LLMs for Qualitative Data Analysis Fail on Security-specificComments in Human Experiments
Maria Camporese, Fabio Massacci, Yuanjun Gong
[Background:] Thematic analysis of free-text justifications in human experiments provides significant qualitative insights. Yet, it is costly because reliable annotations require m…
cs.SE2025
Repairing vulnerabilities without invisible hands. A differentiated replication study on LLMs
Maria Camporese, Fabio Massacci
Background: Automated Vulnerability Repair (AVR) is a fast-growing branch of program repair. Recent studies show that large language models (LLMs) outperform traditional techniques…
cs.SE2025
Using ML filters to help automated vulnerability repairs: when it helps and when it doesn't
Maria Camporese, Fabio Massacci
[Context:] The acceptance of candidate patches in automated program repair has been typically based on testing oracles. Testing requires typically a costly process of building the…