Sumon Biswas

Orcid: 0000-0001-7074-1953

According to our database1, Sumon Biswas authored at least 11 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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On csauthors.net:

Bibliography

2024
Are Prompt Engineering and TODO Comments Friends or Foes? An Evaluation on GitHub Copilot.
Proceedings of the 46th IEEE/ACM International Conference on Software Engineering, 2024

2023
Fix Fairness, Don't Ruin Accuracy: Performance Aware Fairness Repair using AutoML.
Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2023

Towards Safe ML-Based Systems in Presence of Feedback Loops.
Proceedings of the 1st International Workshop on Dependability and Trustworthiness of Safety-Critical Systems with Machine Learned Components, 2023

Towards Understanding Fairness and its Composition in Ensemble Machine Learning.
Proceedings of the 45th IEEE/ACM International Conference on Software Engineering, 2023

Fairify: Fairness Verification of Neural Networks.
Proceedings of the 45th IEEE/ACM International Conference on Software Engineering, 2023

2022
An Empirical Study on the Bugs Found while Reusing Pre-trained Natural Language Processing Models.
CoRR, 2022

23 shades of self-admitted technical debt: an empirical study on machine learning software.
Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2022

The Art and Practice of Data Science Pipelines: A Comprehensive Study of Data Science Pipelines In Theory, In-The-Small, and In-The-Large.
Proceedings of the 44th IEEE/ACM 44th International Conference on Software Engineering, 2022

2021
Fair preprocessing: towards understanding compositional fairness of data transformers in machine learning pipeline.
Proceedings of the ESEC/FSE '21: 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2021

2020
Do the machine learning models on a crowd sourced platform exhibit bias? an empirical study on model fairness.
Proceedings of the ESEC/FSE '20: 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2020

2019
Boa meets python: a boa dataset of data science software in python language.
Proceedings of the 16th International Conference on Mining Software Repositories, 2019


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