Enhancing Trust in LLM-Generated Code Summaries with Calibrated Confidence Scores

arXiv:2404.19318v1 Announce Type: cross
Abstract: A good summary can often be very useful during program comprehension. While a brief, fluent, and relevant summary can be helpful, it does require significant human effort to produce. Often, good summaries are unavailable in software projects, thus making maintenance more difficult. There has been a considerable body of research into automated AI-based methods, using Large Language models (LLMs), to generate summaries of code; there also has been quite a bit work on ways to …

abstract arxiv code confidence cs.cl cs.se generated good human llm maintenance making projects software summary trust type while