ASE 2023

Welcome to the website of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE 2023).

The ASE conference is the premier research forum for Automated Software Engineering. Each year, it brings together researchers and practitioners from academia and industry to discuss foundations, techniques, and tools for automating the analysis, design, implementation, testing, and maintenance of large software systems.

Keynotes

DIDACT: Large sequence models for software development activities

Danny Tarlow

Automating Software Evolution in the Linux Kernel

Julia Lawall

Fault Localization: Research Opportunities and Challenges

Dan Hao

Awarded Papers

	Title
	An Empirical Study on Fine-tuning Large Language Models of Code for Automated Program Repair Research Papers Kai Huang, Xiangxin Meng, Jian Zhang, Yang Liu, Wenjie Wang, Shuhao Li, Yuqing Zhang File Attached
	DeepScaler: Holistic Autoscaling for Microservices Based on Spatiotemporal GNN with Adaptive Graph Learning Research Papers Chunyang Meng, Shijie Song, Haogang Tong, Maolin Pan, Yang Yu Pre-print File Attached
	Detecting Smart Home Automation Application Interferences with Domain Knowledge Research Papers Tao Wang, Wei Chen, Liwei Liu, Guoquan Wu, Jun Wei, Tao Huang Pre-print File Attached
	Domain Adaptive Code Completion via Language Models and Decoupled Domain DatabasesRecorded talk Research Papers Ze Tang, Jidong Ge, Shangqing Liu, Tingwei Zhu, Tongtong Xu, Liguo Huang, Bin Luo Pre-print Media Attached File Attached
	EndWatch: A Practical Method for Detecting Non-Termination in Real-World Software Research Papers Yao Zhang, Xiaofei Xie, Yi Li, Sen Chen, Cen Zhang, Xiaohong Li Pre-print File Attached
	Generative Type Inference for Python Research Papers Yun Peng, Chaozheng Wang, Wenxuan Wang, Cuiyun Gao, Michael Lyu Pre-print File Attached
	LeakPair: Proactive Repairing of Memory Leaks in Single Page Web Applications Research Papers Arooba Shahoor, Askar Yeltayuly Khamit, Jooyong Yi, Dongsun Kim Pre-print Media Attached
	Merge-Replay: Efficient IFDS-Based Taint Analysis by Consolidating Equivalent Value Flows Research Papers Yujiang Gui, Dongjie He, Jingling Xue Pre-print File Attached
	Mutation-based Fault Localization of Deep Neural Networks Research Papers Ali Ghanbari, Deepak-George Thomas, Muhammad Arbab Arshad, Hridesh Rajan Pre-print
	PHYFU: Fuzzing Modern Physics Simulation Engines Research Papers Dongwei Xiao, Zhibo Liu, Shuai Wang Link to publication DOI