ICSE 2026
Sun 12 - Sat 18 April 2026 Rio de Janeiro, Brazil

This program is tentative and subject to change.

Fri 17 Apr 2026 15:15 - 15:30 at Oceania II - Testing and Analysis 19 Chair(s): Nasir Eisty

Regression bugs are common in real-world software projects. Although several studies have characterized various aspects of these bugs, a detailed analysis of the characteristics of code changes that introduce regression bugs is still lacking. It is also not clear whether and how regression bugs can be identified, in the era of wide usage of large language models (LLMs), in code commits during software development in the first place. To fill this gap, our study systematically analyzes 280 regression bugs from open-source Java projects, examining both the root causes and the associated development activities of regression bug-inducing changes, while also evaluating the effectiveness of LLMs in detection such commits and explaining their underlying causes.

Our findings indicate that regression bugs are usually triggered by a single atomic development activity, with feature changes or additions, and bug fixes appearing more frequently in regression bug-inducing commits. Additionally, performance improvements and refactoring are often responsible for the introduction of bugs. We develop a taxonomy that categorizes the root causes of regression bugs into two types: intrinsic errors, such as logic errors and unchecked null references, and compatibility errors, where otherwise correct changes inadvertently violate assumptions or dependencies in other parts of the system.

Furthermore, we verify that LLMs have limited ability to detect regression bugs. Based on our findings, we construct LLM4Reg that substantially improves the precision, recall, and explanation capabilities of LLM-based regression bug detection.

This program is tentative and subject to change.

Fri 17 Apr

Displayed time zone: Brasilia, Distrito Federal, Brazil change

14:00 - 15:30
Testing and Analysis 19Research Track at Oceania II
Chair(s): Nasir Eisty University of Tennessee-Knoxville
14:00
15m
Talk
E-Test: E'er-Improving Test Suites
Research Track
Ketai Qiu USI Università della Svizzera Italiana, Luca Di Grazia University of St. Gallen, Leonardo Mariani University of Milano-Bicocca, Mauro Pezze Università della Svizzera italiana (USI) and Università degli Studi di Milano Bicocca
Pre-print
14:15
15m
Talk
AssertFlip: Reproducing Bugs via Inversion of LLM-Generated Passing Tests
Research Track
Lara Khatib University of Waterloo, Noble Saji Mathews University of Waterloo, Canada, Mei Nagappan University of Waterloo
14:30
15m
Talk
Boosting Gas Revenues of Ethereum Miners
Research Track
Togzhan Barakbayeva HKUST, Soroush Farokhnia Hong Kong University of Science and Technology, Amir Kafshdar Goharshady University of Oxford, Sergei Novozhilov The Hong Kong University of Science and Technology
14:45
15m
Talk
LLM4Perf: Large Language Models Are Effective Samplers for Multi-Objective Performance Modeling
Research Track
Xin Wang The Hong Kong University of Science and Technology (Guangzhou), Zhenhao Li York University, Zishuo Ding The Hong Kong University of Science and Technology (Guangzhou)
Pre-print
15:00
15m
Talk
On the Robustness of Fairness Practices: A Causal Framework for Systematic EvaluationVirtual Attendance
Research Track
Verya Monjezi University of Illinois Chicago, Ashish Kumar Pennsylvania State University, Ashutosh Trivedi University of Colorado Boulder, Gang (Gary) Tan Pennsylvania State University, Saeid Tizpaz-Niari University of Illinois Chicago
15:15
15m
Talk
Characterizing Regression Bug‑Inducing Changes and Improving LLM‑Based Regression Bug DetectionVirtual Attendance
Research Track
Xuezhi Song Fudan University, Yijian Wu Fudan University, Bihuan Chen Fudan University, Zhengjie Lu Fudan University, Shuning Liu Fudan University, Xin Peng Fudan University
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