LLM-generated unit tests with retrieval-augmented context detect faults in 69% of real Python bugs versus 17.2% for general-purpose human-written tests, with similar coverage levels.
Evaluating the effectiveness of llms in fixing maintainability issues in real-world projects
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.SE 2verdicts
UNVERDICTED 2roles
background 1polarities
background 1representative citing papers
Survey mapping LLM applications in software quality assurance to established standards including ISO/IEC 12207, ISO 25010, CMMI, and TMM, with case studies, challenges, and future directions.
citing papers explorer
-
LLM vs. Human Unit Tests: Fault Detection on Real Python Bugs
LLM-generated unit tests with retrieval-augmented context detect faults in 69% of real Python bugs versus 17.2% for general-purpose human-written tests, with similar coverage levels.
-
A Blueprint for AI-Driven Software Quality: Integrating LLMs with Established Standards
Survey mapping LLM applications in software quality assurance to established standards including ISO/IEC 12207, ISO 25010, CMMI, and TMM, with case studies, challenges, and future directions.