6 papers
Is Three the Magic Number? An Empirical Evaluation of LLM-Based Repair Loops
Tobias Kiecker, Eik Reichmann, Hosung Kang +2
Iterative repair loops have become a core design pattern in LLM-based software engineering systems. These workflows repeatedly generate, validate, and repair artifacts using feedba…
Finding the Needle in the Crash Stack: Industrial-Scale Crash Root Cause Localization with AutoCrashFL
Sungmin Kang, Sumi Yun, Jingun Hong +2
Fault Localization (FL) aims to identify root causes of program failures. FL typically targets failures observed from test executions, and as such, often involves dynamic analyses…
Identifying Bug Inducing Commits by Combining Fault Localisation and Code Change Histories
Gabin An, Jinsu Choi, Jingun Hong +2
A Bug Inducing Commit (BIC) is a code change that introduces a bug into the codebase. Although the abnormal or unexpected behavior caused by the bug may not manifest immediately, i…
COSMosFL: Ensemble of Small Language Models for Fault Localisation
Hyunjoon Cho, Sungmin Kang, Gabin An +1
LLMs are rapidly being adopted to build powerful tools and agents for software engineering, but most of them rely heavily on extremely large closed-source models. This, in turn, ca…
METAMON: Finding Inconsistencies between Program Documentation and Behavior using Metamorphic LLM Queries
Hyeonseok Lee, Gabin An, Shin Yoo
Code documentation can, if written precisely, help developers better understand the code they accompany. However, unlike code, code documentation cannot be automatically verified v…
Lachesis: Predicting LLM Inference Accuracy using Structural Properties of Reasoning Paths
Naryeong Kim, Sungmin Kang, Gabin An +1
Large Language Models are increasingly used to build agents to perform more complex tasks. As LLMs perform more complicated reasoning through longer interactions, self-consistency,…