Toward Efficient Software Engineering Automation Advancing Efficient and Sustainable Software Engineering Automation via, Quantization, Knowledge Distillation and PEFT Interpretable Neurosymbolic Software Engineering Decoding the Synergy of Neural and Symbolic Systems in Software Engineering Extra Functional Requirements of Large Code Models Unveiling the Hidden Challenges of LCMs--Robustness, Trustworthiness and Security Towards Intelligent and Scalable Software Documentation Practices via with Multi-Agent LLMs Beyond Snippets — Challenges in Reasoning, Integration, and Coherence in Multi-Agent LLMs for Code Understanding
