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Highlights of “Challenges in Migrating Imperative Deep Learning Programs to Graph Execution: An Empirical Study”

In this blog post, we summarize, using code examples, our recent empirical study on challenges in migrating imperative Deep Learning programs to graph execution.


Video of ICSE ’21 talk now available

A video of our ICSE 2021 talk on “An Empirical Study of Refactorings and Technical Debt in Machine Learning Systems” is now available!

Actor concurrency study paper accepted at OOPSLA 2020

I am excited to announce that our paper, entitled “Actor Concurrency Bugs: A Comprehensive Study on Symptoms, Root Causes, API Usages, and Differences,” was accepted at OOPSLA 2020! One hundred nine papers were approved out of 302 submissions, amounting to a 36% acceptance rate.

Preprint now available for FASE 2020 paper

A preprint of our FASE 2020 paper entitled, “An Empirical Study on the Use and Misuse of Java 8 Streams,” is now available.

Raw data for an Empirical Study on the Use and Misuse of Java 8 Streams

Raw data for our empirical study on the use and misuse of Java 8 streams is now available. See the project page for more details on the study.

Preprint now available for Proactive Empirical Assessment paper

A preprint version of our paper entitled, “Proactive Empirical Assessment of New Language Feature Adoption via Automated Refactoring: The Case of Java 8 Default Methods,” to appear later this year at <Programming> 2018, is now available.

Talk at IBM Programming Languages Day 2017 on December 4

I will be giving a talk at the 2017 IBM Programming Languages Day on December 4 at the IBM T.J. Watson Research Center in Yorktown Heights, NY. I will be discussing our recent work on empirically assessing new language features proactively via automated refactoring.

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