ICSME 2023 (series) / Journal First Track /
An annotation-based approach for finding bugs in neural network programs
Thu 5 Oct 2023 16:02 - 16:18 at Session 1 Room - RGD 004 - Software Faults Chair(s): Masud Rahman, Ashkan Sami
Thu 5 OctDisplayed time zone: Bogota, Lima, Quito, Rio Branco change
Thu 5 Oct
Displayed time zone: Bogota, Lima, Quito, Rio Branco change
15:30 - 17:00 | Software FaultsIndustry Track / Research Track / Journal First Track at Session 1 Room - RGD 004 Chair(s): Masud Rahman Dalhousie University, Ashkan Sami Edinburgh Napier University | ||
15:30 16mTalk | An Empirical Study on Fault Diagnosisa in Robotic Systems Research Track Xuezhi Song Fudan University, Yi Li , Zhen Dong Fudan University, China, Shuning Liu Fudan University, Junming Cao Fudan University, Xin Peng Fudan University | ||
15:46 16mTalk | Predicting Defective Visual Code Changes in a Multi-Language AAA Video Game Project Industry Track Pre-print | ||
16:02 16mTalk | An annotation-based approach for finding bugs in neural network programs Journal First Track Mohammad Rezaalipour Software Institute @ USI, Carlo A. Furia Università della Svizzera italiana (USI) | ||
16:18 11mTalk | Evaluation of Cross-Lingual Bug Localization: Two Industrial Cases Industry Track Shinpei Hayashi Tokyo Institute of Technology, Takashi Kobayashi Tokyo Institute of Technology, Tadahisa Kato Hitachi, Ltd. DOI Pre-print | ||
16:29 16mTalk | An Empirical Study on Bugs Inside PyTorch: A Replication Study Research Track Sharon Chee Yin Ho Concordia University, Vahid Majdinasab Polytechnique Montréal, Mohayeminul Islam University of Alberta, Diego Costa Concordia University, Canada, Emad Shihab Concordia Univeristy, Foutse Khomh Polytechnique Montréal, Sarah Nadi University of Alberta, Muhammad Raza Queen's University | ||
16:45 15mLive Q&A | 1:1 Q&A Research Track |