97 citations · 308 across the 8 of their papers we have counts for
8 papers
ReqGenX: An Empirical Study of Atomic Decomposition, Artifact Regeneration, and Reconstruction for Legacy SRS Documents
Ragib Shahariar Ayon, Rayed Fahmi, Sumon Biswas +1
Background: Evaluating automated Software Requirements Specification (SRS) generation is challenging because few datasets provide fine-grained traceability between source requireme…
Fix Fairness, Don't Ruin Accuracy: Performance Aware Fairness Repair using AutoML
Giang Nguyen, Sumon Biswas, Hridesh Rajan
Machine learning (ML) is increasingly being used in critical decision-making software, but incidents have raised questions about the fairness of ML predictions. To address this iss…
Fairify: Fairness Verification of Neural Networks
Sumon Biswas, Hridesh Rajan
Fairness of machine learning (ML) software has become a major concern in the recent past. Although recent research on testing and improving fairness have demonstrated impact on rea…
Towards Understanding Fairness and its Composition in Ensemble Machine Learning
Usman Gohar, Sumon Biswas, Hridesh Rajan
Machine Learning (ML) software has been widely adopted in modern society, with reported fairness implications for minority groups based on race, sex, age, etc. Many recent works ha…
An Empirical Study on the Bugs Found while Reusing Pre-trained Natural Language Processing Models
Rangeet Pan, Sumon Biswas, Mohna Chakraborty +2
In NLP, reusing pre-trained models instead of training from scratch has gained popularity; however, NLP models are mostly black boxes, very large, and often require significant res…
The Art and Practice of Data Science Pipelines: A Comprehensive Study of Data Science Pipelines In Theory, In-The-Small, and In-The-Large
Sumon Biswas, Mohammad Wardat, Hridesh Rajan
Increasingly larger number of software systems today are including data science components for descriptive, predictive, and prescriptive analytics. The collection of data science s…
Fair Preprocessing: Towards Understanding Compositional Fairness of Data Transformers in Machine Learning Pipeline
Sumon Biswas, Hridesh Rajan
In recent years, many incidents have been reported where machine learning models exhibited discrimination among people based on race, sex, age, etc. Research has been conducted to…
Do the Machine Learning Models on a Crowd Sourced Platform Exhibit Bias? An Empirical Study on Model Fairness
Sumon Biswas, Hridesh Rajan
Machine learning models are increasingly being used in important decision-making software such as approving bank loans, recommending criminal sentencing, hiring employees, and so o…