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Tag Archives: empirical software engineering
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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.
Continue Reading →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.
