ICSE 2024
Fri 12 - Sun 21 April 2024 Lisbon, Portugal
Fri 19 Apr 2024 10:30 - 11:00 at Open Space - Posters 5

In deep learning applications, robustness measures the ability of neural models that handle slight changes in input data, which could lead to potential safety hazards, especially in safety-critical applications. Pre-deployment assessment of model robustness is essential, but existing methods often suffer from either high costs or imprecise results. To enhance safety in real-world scenarios, metrics that effectively capture the model’s robustness are needed. To address this issue, we compare the rigour and usage conditions of various assessment methods based on different definitions. Then, we propose a straightforward and practical metric utilizing hypothesis testing for probabilistic robustness and have integrated it into the TorchAttacks library. Through a comparative analysis of diverse robustness assessment methods, our approach contributes to a deeper understanding of model robustness in safety-critical applications.

Fri 19 Apr

Displayed time zone: Lisbon change

10:30 - 11:00
Posters 5Posters at Open Space
10:30
30m
Poster
Exploring the Effectiveness of LLM based Test-driven Interactive Code Generation: User Study and Empirical Evaluation
Posters
Sarah Fakhoury Microsoft Research, Aaditya Naik University of Pennsylvania, Georgios Sakkas University of California at San Diego, Saikat Chakraborty Microsoft Research, Madan Musuvathi Microsoft Research, Shuvendu K. Lahiri Microsoft Research
10:30
30m
Poster
On the Need for Empirically Investigating Fast-Growing Programming Languages
Posters
Jahnavi Kumar Indian Institute of Technology Tirupati, India, Sridhar Chimalakonda Indian Institute of Technology, Tirupati
10:30
30m
Poster
Decoding Log Parsing Challenges: A Comprehensive Taxonomy for Actionable Solutions
Posters
Issam Sedki Concordia University, Wahab Hamou-Lhadj Concordia University, Montreal, Canada, Otmane Ait-Mohamed Concordia University, Naser Ezzati Jivan , Mohammed Shehab Concordia University
10:30
30m
Poster
Automated Code Editing with Search-Generate-Modify
Posters
Changshu Liu Columbia University, Pelin Cetin Columbia University, Yogesh Patodia Columbia University, Baishakhi Ray AWS AI Labs, Saikat Chakraborty Microsoft Research, Yangruibo Ding Columbia University
10:30
30m
Poster
Exploring the Impact of Inheritance on Test Code Maintainability
Posters
Dong Jae Kim Concordia University, Tse-Hsun (Peter) Chen Concordia University
10:30
30m
Poster
Improving Program Debloating with 1-DU Chain Minimality
Posters
Myeongsoo Kim Georgia Institute of Technology, Santosh Pande Georgia Institute of Technology, Alessandro Orso Georgia Institute of Technology
Pre-print
10:30
30m
Poster
GoSpeechLess: Interoperable Serverless ML-based Cloud Services
Posters
Sashko Ristov University of Innsbruck, Philipp Gritsch University of Innsbruck, David Meyer University of Innsbruck, Michael Felderer German Aerospace Center (DLR) & University of Cologne
10:30
30m
Poster
Towards Precise Observations of Neural Model Robustness in Classification
Posters
Wenchuan Mu ISTD, Singapore University of Technology and Design, Kwan Hui Lim Singapore University of Technology and Design, Singapore
10:30
30m
Poster
Assessing AI-Based Code Assistants in Method Generation Tasks
Posters
Vincenzo Corso University of Milano - Bicocca, Leonardo Mariani University of Milano-Bicocca, Daniela Micucci University of Milano-Bicocca, Italy, Oliviero Riganelli University of Milano - Bicocca
10:30
30m
Poster
Recovering Traceability Links between Release Notes and Related Software Artifacts
Posters
Sristy Sumana Nath University of Saskatchewan, Banani Roy University of Saskatchewan
10:30
30m
Poster
Improving the Condensing of Reverse Engineered Class Diagrams using Weighted Network Metrics
Posters
Weifeng Pan Zhejiang Gongshang University, Wei Wu Zhejiang Gongshang University, Hua Ming Oakland University, Dae-Kyoo Kim Oakland University, Jinkai Yang Oakland University, Ruochen Liu Oakland University
Media Attached
10:30
30m
Poster
Exploring Data Cleanness in Defects4J and Its Influence on Fault Localization Efficiency
Posters
Md Nakhla Rafi Concordia University, An Ran Chen University of Alberta, Tse-Hsun (Peter) Chen Concordia University, Shaohua Wang Central University of Finance and Economics
10:30
30m
Poster
Learning to Represent Patches
Posters
Xunzhu Tang University of Luxembourg, Haoye Tian University of Melbourne, Zhenghan Chen Peking University, Weiguo Pian University of Luxembourg, Saad Ezzini Lancaster University, Abdoul Kader Kaboré University of Luxembourg, Andrew Habib ABB Corporate Research, Germany, Jacques Klein University of Luxembourg, Tegawendé F. Bissyandé University of Luxembourg
10:30
30m
Poster
Bringing Structure to Naturalness: On the Naturalness of ASTs
Posters
Profir-Petru Pârțachi National Institute of Informatics, Japan, Mahito Sugiyama National Institute of Informatics, Japan