Toward more dependable software and AI

Selected Papers

Boa: A Language and Infrastructure for Analyzing Ultra-Large-Scale Software Repositories

ICSE '13

A Comprehensive Study on Deep Learning Bug Characteristics

ESEC-FSE '19

Ptolemy: A Language with Quantified Typed, Events

ECOOP '08

DeepLocalize: Fault Localization for Deep Neural Networks

ICSE '21

On Decomposing a Deep Neural Network into Modules

ESEC-FSE '20

RefineAct: Automatic Runtime Verification of LLM Agent Actions

ASE '26

IRepair: An Intent-Aware Approach to Repair Data-Driven Errors in Large Language Models

FSE '25

µPRL: A Mutation Testing Pipeline for Deep Reinforcement Learning based on Real Faults

ICSE '25

An LLM-Based Agent-Oriented Approach for Automated Code Design Issue Localization

ICSE '25

Mock Deep Testing: Toward Separate Development of Data and Models for Deep Learning

ICSE '25

Inferring Data Preconditions from Deep Learning Models for Trustworthy Prediction in Deployment

ICSE '24

Are Prompt Engineering and TODO Comments Friends or Foes? An Evaluation on GitHub Copilot

ICSE '24

Data-Driven Evidence-Based Syntactic Sugar Design

ICSE '24

Design by Contract for Deep Learning APIs

ESEC-FSE '23

Fix Fairness, Don’t Ruin Accuracy: Performance Aware Fairness Repair using AutoML

ESEC-FSE '23

Fairify: Fairness Verification of Neural Networks

ICSE '23

Decomposing a Recurrent Neural Network into Modules for Enabling Reusability and Replacement

ICSE '23

Towards Understanding Fairness and its Composition in Ensemble Machine Learning

ICSE '23

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