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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.…
Characterizing Faults in Agentic AI: A Taxonomy of Types, Symptoms, and Root Causes
Mehil B Shah, Mohammad Mehdi Morovati, Mohammad Masudur Rahman +1
Agentic AI systems combine LLM-based reasoning, orchestration, tool invocation, and interaction with external environments. These systems introduce faults that are difficult to cha…
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…
Improved Detection and Diagnosis of Faults in Deep Neural Networks Using Hierarchical and Explainable Classification
Sigma Jahan, Mehil B Shah, Parvez Mahbub +1
Deep Neural Networks (DNN) have found numerous applications in various domains, including fraud detection, medical diagnosis, facial recognition, and autonomous driving. However, D…
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 Understanding the Challenges of Bug Localization in Deep Learning Systems
Sigma Jahan, Mehil B. Shah, Mohammad Masudur Rahman
Software bugs cost the global economy billions of dollars annually and claim ~50\% of the programming time from software developers. Locating these bugs is crucial for their resolu…
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…