ICSE 2024
Fri 12 - Sun 21 April 2024 Lisbon, Portugal

Large Language Models (LLMs) promise strategic benefit for numerous application domains. The current state-of-the-art in LLMs, however, lacks the trust, security, and reliability which prohibits their use in high stakes applications. To address this, our work investigated the challenges of developing, deploying, and assessing LLMs within a specific high stakes application, intelligence reporting workflows. We identified the following challenges that need to be addressed before LLMs can be used in high stakes applications: (1) challenges with unverified data and data leakage, (2) challenges with fine tuning and inference at scale, and (3) challenges in reproducibility and assessment of LLMs. We argue that researchers should prioritize test and assessment metrics, as better metrics will lead to insight to further improve these LLMs.

Wed 17 Apr

Displayed time zone: Lisbon change

16:00 - 17:30
16:00
15m
Talk
Large Language Models for Test-Free Fault Localization
Research Track
Aidan Z.H. Yang Carnegie Mellon University, Claire Le Goues Carnegie Mellon University, Ruben Martins Carnegie Mellon University, Vincent J. Hellendoorn Carnegie Mellon University
16:15
15m
Talk
Dataflow Analysis-Inspired Deep Learning for Efficient Vulnerability Detection
Research Track
Benjamin Steenhoek Iowa State University, Hongyang Gao Dept. of Computer Science, Iowa State University, Wei Le Iowa State University
Pre-print
16:30
15m
Talk
An Empirical Study on Compliance with Ranking Transparency in the Software Documentation of EU Online Platforms
Software Engineering in Society
Francesco Sovrano University of Zurich, Michaël Lognoul University of Namur (CRIDS, NADI), Alberto Bacchelli University of Zurich
16:45
15m
Talk
An Industry Case Study on Adoption of AI-based Programming Assistants
Software Engineering in Practice
Nicole Davila Universidade Federal do Rio Grande do Sul, Igor Wiese Federal University of Technology, Igor Steinmacher Northern Arizona University, Lucas Lucio Federal University of Technology - Paraná (UTFPR), André Kawamoto Federal University of Technology - Paraná (UTFPR), Gilson José Peres Favaro , Ingrid Nunes Universidade Federal do Rio Grande do Sul (UFRGS), Brazil
17:00
7m
Talk
Assessing LLMs for High Stakes Applications
Software Engineering in Practice
Shannon K. Gallagher Software Engineering Institute, Carnegie Mellon University, Jasmine Ratchford Software Engineering Institute, Carnegie Mellon University, Tyler Brooks Software Engineering Institute, Carnegie Mellon University, Bryan P. Brown Software Engineering Institute, Carnegie Mellon University, Eric Heim Software Engineering Institute, Carnegie Mellon University, William R. Nichols Software Engineering Institute, Carnegie Mellon University, Scott McMillan Software Engineering Institute, Carnegie Mellon University, Swati Rallapalli Software Engineering Institute, Carnegie Mellon University, Carol J. Smith Software Engineering Institute, Carnegie Mellon University, Nathan VanHoudnos Software Engineering Institute, Carnegie Mellon University, Nick Winski Software Engineering Institute, Carnegie Mellon University, Andrew O. Mellinger Software Engineering Institute, Carnegie Mellon University
17:07
7m
Talk
ITG: Trace Generation via Iterative Interaction between LLM Query and Trace Checking
New Ideas and Emerging Results
Weilin Luo SUN YAT-SEN UNIVERSITY, Weiyuan Fang SUN YAT-SEN UNIVERSITY, Junming Qiu SUN YAT-SEN UNIVERSITY, Hai Wan School of Data and Computer Science, Sun Yat-sen University, Yanan Liu SUN YAT-SEN UNIVERSITY, Rongzhen Ye Sun Yat-Sen University
17:14
7m
Talk
Improving Cross-Language Code Clone Detection via Code Representation Learning and Graph Neural Networks
Journal-first Papers
NIKITA MEHROTRA Indraprastha Institute of Information Technology, Akash Sharma IIIT-Delhi, Anmol Jindal IIIT-Delhi, Rahul Purandare UNL, USA