26 citations · 50 across the 6 of their papers we have counts for
6 papers
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…
Predicting Line-Level Defects by Capturing Code Contexts with Hierarchical Transformers
Parvez Mahbub, Mohammad Masudur Rahman
Software defects consume 40% of the total budget in software development and cost the global economy billions of dollars every year. Unfortunately, despite the use of many software…
Bugsplainer: Leveraging Code Structures to Explain Software Bugs with Neural Machine Translation
Parvez Mahbub, Mohammad Masudur Rahman, Ohiduzzaman Shuvo +1
Software bugs cost the global economy billions of dollars each year and take up ~50% of the development time. Once a bug is reported, the assigned developer attempts to identify an…
Defectors: A Large, Diverse Python Dataset for Defect Prediction
Parvez Mahbub, Ohiduzzaman Shuvo, Mohammad Masudur Rahman
Defect prediction has been a popular research topic where machine learning (ML) and deep learning (DL) have found numerous applications. However, these ML/DL-based defect predictio…
Authorship Identification of Source Code Segments Written by Multiple Authors Using Stacking Ensemble Method
Parvez Mahbub, Naz Zarreen Oishie, S M Rafizul Haque
Source code segment authorship identification is the task of identifying the author of a source code segment through supervised learning. It has vast importance in plagiarism detec…
Explaining Software Bugs Leveraging Code Structures in Neural Machine Translation
Parvez Mahbub, Ohiduzzaman Shuvo, Mohammad Masudur Rahman
Software bugs claim approximately 50% of development time and cost the global economy billions of dollars. Once a bug is reported, the assigned developer attempts to identify and u…