ICSE 2024
Fri 12 - Sun 21 April 2024 Lisbon, Portugal
Fri 19 Apr 2024 11:30 - 11:45 at Grande Auditório - LLM, NN and other AI technologies 5 Chair(s): Baishakhi Ray

Text-to-SQL, the task of translating natural language questions into SQL queries, is part of various business processes. Its automation, which is an emerging challenge, will empower software practitioners to seamlessly interact with relational databases using natural language, thereby bridging the gap between business needs and software capabilities. In this paper, we consider Large Language Models (LLMs), which have achieved state of the art for various NLP tasks. Specifically, we benchmark Text-to-SQL performance, the evaluation methodologies, as well as input optimization (e.g., prompting). In light of the empirical observations that we have made, we propose two novel metrics that were designed to adequately measure the similarity between SQL queries. Overall, we share with the community various findings, notably on how to select the right LLM on Text-to-SQL tasks. We further demonstrate that a tree-based edit distance constitutes a reliable metric for assessing the similarity between generated SQL queries and the oracle for benchmarking Text2SQL approaches. This metric is important as it relieves researchers from the need to perform computationally expensive experiments such as executing generated queries as done in prior works. Our work implements financial domain use cases and, therefore contributes to the advancement of Text2SQL systems and their practical adoption in this domain.

Fri 19 Apr

Displayed time zone: Lisbon change

11:00 - 12:30
11:00
15m
Talk
Enhancing Exploratory Testing by Large Language Model and Knowledge Graph
Research Track
Yanqi Su Australian National University, Dianshu Liao Australian National University, Zhenchang Xing CSIRO's Data61, Qing Huang School of Computer Information Engineering, Jiangxi Normal University, Mulong Xie CSIRO's Data61, Qinghua Lu Data61, CSIRO, Xiwei (Sherry) Xu Data61, CSIRO
11:15
15m
Talk
LLMParser: An Exploratory Study on Using Large Language Models for Log Parsing
Research Track
Zeyang Ma Concordia University, An Ran Chen University of Alberta, Dong Jae Kim Concordia University, Tse-Hsun (Peter) Chen Concordia University, Shaowei Wang Department of Computer Science, University of Manitoba, Canada
11:30
15m
Talk
Enhancing Text-to-SQL Translation for Financial System Design
Software Engineering in Practice
Yewei Song University of Luxembourg, Saad Ezzini Lancaster University, Xunzhu Tang University of Luxembourg, Cedric Lothritz University of Luxembourg, Jacques Klein University of Luxembourg, Tegawendé F. Bissyandé University of Luxembourg, Andrey Boytsov Banque BGL BNP Paribas, Ulrick Ble Banque BGL BNP Paribas, Anne Goujon Banque BGL BNP Paribas
11:45
15m
Talk
Towards Building AI-CPS with NVIDIA Isaac Sim: An Industrial Benchmark and Case Study for Robotics Manipulation
Software Engineering in Practice
Zhehua Zhou University of Alberta, Jiayang Song University of Alberta, Xuan Xie University of Alberta, Zhan Shu University of Alberta, Lei Ma The University of Tokyo & University of Alberta, Dikai Liu NVIDIA AI Tech Centre, Jianxiong Yin NVIDIA AI Tech Centre, Simon See NVIDIA AI Tech Centre
Pre-print
12:00
15m
Talk
Let's Ask AI About Their Programs: Exploring ChatGPT's Answers To Program Comprehension Questions
Software Engineering Education and Training
Teemu Lehtinen Aalto University, Charles Koutcheme Aalto University, Arto Hellas Aalto University
Pre-print Media Attached File Attached
12:15
15m
Talk
Experience Report: Identifying common misconceptions and errors of novice programmers with ChatGPT
Software Engineering Education and Training
Hua Leong Fwa Singapore Management University
Media Attached