ICSE 2024
Fri 12 - Sun 21 April 2024 Lisbon, Portugal
Fri 19 Apr 2024 17:07 - 17:14 at Almada Negreiros - Language Models and Generated Code 4 Chair(s): Shin Yoo

It is expected that in the near future, AI software development assistants will play an important role in the software industry. However, current AI SD assistants tend to be unreliable, often producing incorrect, unsafe, or low-quality code. We seek to resolve these issues by introducing a holistic architecture for constructing, training, and using trustworthy AI software development assistants. In the center of the architecture, there is a foundational LLM trained on datasets representative of real-world coding scenarios and complex software architectures, and fine-tuned on code quality criteria beyond correctness. The LLM will make use of graph-based code representations for advanced semantic comprehension. We envision a knowledge graph integrated into the system to provide up-to-date background knowledge and to enable the assistant to provide appropriate explanations. Finally, a modular framework for constrained decoding will ensure that certain guarantees (e.g., for correctness and security) hold for the generated code.

Fri 19 Apr

Displayed time zone: Lisbon change

16:00 - 17:30
Language Models and Generated Code 4New Ideas and Emerging Results / Research Track at Almada Negreiros
Chair(s): Shin Yoo Korea Advanced Institute of Science and Technology
16:00
15m
Talk
Lost in Translation: A Study of Bugs Introduced by Large Language Models while Translating Code
Research Track
Rangeet Pan IBM Research, Ali Reza Ibrahimzada University of Illinois Urbana-Champaign, Rahul Krishna IBM Research, Divya Sankar IBM Research, Lambert Pouguem Wassi IBM Research, Michele Merler IBM Research, Boris Sobolev IBM Research, Raju Pavuluri IBM T.J. Watson Research Center, Saurabh Sinha IBM Research, Reyhaneh Jabbarvand University of Illinois at Urbana-Champaign
DOI Pre-print Media Attached
16:15
15m
Talk
Traces of Memorisation in Large Language Models for Code
Research Track
Ali Al-Kaswan Delft University of Technology, Netherlands, Maliheh Izadi Delft University of Technology, Arie van Deursen Delft University of Technology
Pre-print
16:30
15m
Talk
Language Models for Code Completion: A Practical Evaluation
Research Track
Maliheh Izadi Delft University of Technology, Jonathan Katzy Delft University of Technology, Tim van Dam Delft University of Technology, Marc Otten Delft University of Technology, Răzvan Mihai Popescu Delft University of Technology, Arie van Deursen Delft University of Technology
Pre-print
16:45
15m
Talk
Evaluating Large Language Models in Class-Level Code Generation
Research Track
Xueying Du Fudan University, Mingwei Liu Fudan University, Kaixin Wang Fudan University, Hanlin Wang Fudan University, Junwei Liu Huazhong University of Science and Technology, Yixuan Chen Fudan University, Jiayi Feng Fudan University, Chaofeng Sha Fudan University, Xin Peng Fudan University, Yiling Lou Fudan University
Pre-print
17:00
7m
Talk
Naturalness of Attention: Revisiting Attention in Code Language Models
New Ideas and Emerging Results
Mootez Saad Dalhousie University, Tushar Sharma Dalhousie University
Pre-print
17:07
7m
Talk
Towards Trustworthy AI Software Development Assistance
New Ideas and Emerging Results
Daniel Maninger TU Darmstadt, Krishna Narasimhan TU Darmstadt, Mira Mezini TU Darmstadt
DOI Pre-print