5 papers
Imitation Game: Reproducing Deep Learning Bugs Leveraging an Intelligent Agent
Mehil B Shah, Mohammad Masudur Rahman, Foutse Khomh
Despite their wide adoption in various domains (e.g., healthcare, finance, software engineering), Deep Learning (DL)-based applications suffer from many bugs, failures, and vulnera…
Be a Partner, not a Bystander in Software Engineering Practice: Bridging the Gaps between Academia and Industry
Mohammad Masudur Rahman, Mehil B. Shah
Software engineering conferences bring together thousands of academicians and software practitioners so that academic research and professional practices can influence each other.…
Surgeons Are Indian Males and Speech Therapists Are White Females: Auditing Biases in Vision-Language Models for Healthcare Professionals
Zohaib Hasan Siddiqui, Dayam Nadeem, Mohammad Masudur Rahman +3
Vision language models (VLMs), such as CLIP and OpenCLIP, can encode and reflect stereotypical associations between medical professions and demographic attributes learned from web-…
Towards Understanding the Impact of Data Bugs on Deep Learning Models in Software Engineering
Mehil B Shah, Mohammad Masudur Rahman, Foutse Khomh
Deep learning (DL) techniques have achieved significant success in various software engineering tasks (e.g., code completion by Copilot). However, DL systems are prone to bugs from…
Towards Enhancing the Reproducibility of Deep Learning Bugs: An Empirical Study
Mehil B. Shah, Mohammad Masudur Rahman, Foutse Khomh
Context: Deep learning has achieved remarkable progress in various domains. However, like any software system, deep learning systems contain bugs, some of which can have severe imp…