3 accepted papers
Large Language Model (LLM) agents have demonstrated remarkable proficiency in solving isolated software engineering tasks. However, existing benchmarks predominantly evaluate static, independent issues, failing to reflect the continuous and sequentially dependent nature of real-world software evolut…
Code localization–identifying precisely where in a codebase changes need to be made–is a fundamental yet challenging task in software maintenance. Existing approaches struggle to efficiently navigate complex codebases when identifying relevant code snippets.The challenge lies in bridging natural lan…
Heterophilous graphs, where dissimilar nodes tend to connect, pose a challenge for graph neural networks (GNNs). Increasing the GNN depth can expand the scope (i.e., receptive field), potentially finding homophily from the higher-order neighborhoods. However, GNNs suffer from performance degradation…