Select Papers

The Art and Practice of Data Science Pipelines: A Comprehensive Study of Data Science Pipelines In Theory, In-The-Small, and In-The-Large

ICSE '22

Decomposing Convolutional Neural Networks into Reusable and Replaceable Modules

ICSE '22

DeepDiagnosis: Automatically Diagnosing Faults and Recommending Actionable Fixes in Deep Learning Programs

ICSE '22

Manas: Mining Software Repositories to Assist AutoML

ICSE '22

Semantics and Anomaly Preserving Sampling Strategy for Large-Scale Time Series Data

TDS '22

Fair Preprocessing: Towards Understanding Compositional Fairness of Data Transformers in Machine Learning Pipeline

ESEC-FSE '21

On Decomposing a Deep Neural Network into Modules

ESEC-FSE '20

Do the Machine Learning Models on a Crowd Sourced Platform Exhibit Bias? An Empirical Study on Model Fairness

ESEC-FSE '20

Repairing Deep Neural Networks Fix Patterns and Challenges

ICSE '20

BCFA Bespoke Control Flow Analysis for CFA at Scale

ICSE '20

A Comprehensive Study on Deep Learning Bug Characteristics

ESEC-FSE '19

Large-scale Study of Substitutability in the Presence of Effects

FSE '18

Collective Program Analysis

ICSE '18

Are Code Examples on an Online Q&A Forum Reliable? A Study of API Misuse on Stack Overflow

ICSE '18

Exploiting Implicit Beliefs to Resolve Sparse Usage Problem in Usage-based Specification Mining

OOPSLA '17

On Accelerating Ultra-Large-Scale Mining

ICSE '17 (NIER)

Capsule-Oriented Programming

ICSE '15 (NIER)

Boa: Ultra-Large-Scale Software Repository and Source-Code Mining

TOSEM '15

Inferring Behavioral Specifications from Large-scale Repositories by Leveraging Collective Intelligence

ICSE '15 (NIER)

First-Class Effect Reflection for Effect-Guided Programming

OOPSLA '16

Intensional Effect Polymorphism

ECOOP '15

Effectively Mapping Linguistic Abstractions for Message-passing Concurrency to Threads on the Java Virtual Machine

OOPSLA '15

News

Our work on Decomposing Convolutional Neural Networks into Reusable and Replaceable Modules selected for ICSE'22

December 10, 2021

In this paper, we propose an approach to decompose a convolutional neural network (CNN) model used for image classification into modules, in which each module...

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Our paper on Data Science Pipeline is selected for ICSE'22 Research Track

December 03, 2021

This work attempts to inform the art and practice of designing data science (DS) pipeline. Our investigation suggest that DS pipeline is a well used...

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Sumon Biswas defends MS thesis

November 04, 2021

Sumon Biswas has successfully defended his MS thesis entitled “Understanding Unfairness and its Mitigation in Open-Source Machine Learning Models”. The abstract of the thesis is...

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Our paper on Fair Preprocessing is selected for ESEC/FSE'21 Research Track

May 20, 2021

This work proposed a causal method to measure fairness of components in machine learning pipeline. Specifically, it evaluates many preprocessing stages in the pipeline and...

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ACM SIGSOFT Distinguished Paper Award at ESEC/FSE 2020

August 20, 2020

PhD student Rangeet Pan and Hridesh Rajan have received an ACM SIGSOFT Distinguished Paper Award at the ACM Joint European Software Engineering Conference and Symposium...

Pan earns 2nd Place at the ACM Student Research Competition at the International Conference on Software Engineering (ICSE)

July 30, 2020

Graduate student Rangeet Pan earned second place at the ACM Student Research Competition at 42nd International Conference on Software Engineering (ICSE) 2020 for his work...

Alumni Mehdi Bagherzadeh receives EAPLS Best Paper Award

July 29, 2020

The EAPLS Best Paper Award 2020 is awarded to the paper “An Empirical Study on the Use and Misuse of Java 8 Streams”, by Raffi...

Md Johirul Islam defends PhD thesis

July 15, 2020

Md Johirul Islam has successfully defended his PhD thesis entitled “Towards Understanding the Challenges Faced by Machine Learning Software Developers and Enabling Automated Solutions”. The...

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Our paper on decomposing a Deep Neural Network into Modules is selected for ESEC/FSE'20

May 19, 2020

This work presents takes the first step toward decomposing a monolithic deep neural network (DNN) into modules so that components of the deep neural network...

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Our paper on Empirical Study on Model Fairness is selected for ESEC/FSE'20

May 19, 2020

This work presents a comprehensive study of machine learning models to understand whether they exhibit bias. The paper’s abstract: ``Machine learning models are increasingly being...

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