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How Effective are Large Language Models in Generating Software Specifications?
Danning Xie, Byungwoo Yoo, Nan Jiang +4
Software specifications are essential for many Software Engineering (SE) tasks such as bug detection and test generation. Many existing approaches are proposed to extract the speci…
Symbol Preference Aware Generative Models for Recovering Variable Names from Stripped Binary
Xiangzhe Xu, Zhuo Zhang, Zian Su +8
Decompilation aims to recover the source code form of a binary executable. It has many security applications, such as malware analysis, vulnerability detection, and code hardening.…
A Syntax-Guided Multi-Task Learning Approach for Turducken-Style Code Generation
Guang Yang, Yu Zhou, Xiang Chen +4
Due to the development of pre-trained language models, automated code generation techniques have shown great promise in recent years. However, the generated code is difficult to me…
KNOD: Domain Knowledge Distilled Tree Decoder for Automated Program Repair
Nan Jiang, Thibaud Lutellier, Yiling Lou +3
Automated Program Repair (APR) improves software reliability by generating patches for a buggy program automatically. Recent APR techniques leverage deep learning (DL) to build mod…
PyART: Python API Recommendation in Real-Time
Xincheng He, Lei Xu, Xiangyu Zhang +3
API recommendation in real-time is challenging for dynamic languages like Python. Many existing API recommendation techniques are highly effective, but they mainly support static l…