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Slides for ASE ’23 NIER paper on imperative Deep Learning refactoring now available

Slides for our ASE ’23 NIER paper on our ongoing work towards automated refactoring of imperative Deep Learning programs to graph execution are now available. The talk will take place tomorrow at 1:54 pm CEST.

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Preprint of ASE ’23 DL refactoring paper now available

A preprint of our ASE ’23 paper on refactoring imperative Deep Learning programs to graphs is now available.

Paper on refactoring imperative Deep Learning programs to graphs accepted at ASE ’23 NIER

Our paper entitled, “Towards Safe Automated Refactoring of Imperative Deep Learning Programs to Graph Execution” has been accepted to the New Ideas and Emerging Results (NIER) track at the IEEE/ACM 2023 International Conference on Automated Software Engineering (ASE)! Out of 70 papers, 25 were accepted, amounting to a 35.7% acceptance rate. The conference will take place later this year in Kirchberg, Luxembourg.

Congratulations to Tatiana, Mehdi, Nan, and Anita, and thank you for all of your hard work!

Alexi Turcotte from Northeastern visits CUNY

Alexi Turcotte (website) from Northeastern University visited CUNY last week and gave a talk on asynchronous JavaScript at our graduate student event at the CUNY Graduate center. Alexi is a 5th year Ph.D. candidate at Northeastern University. Frank Tip and Jan Vitek advise him; with Frank, he works on optimizing asynchronous JavaScript programs; with Jan, he works on fuzzing and type system design for the R programming language. He is interested in anything related to dynamic and data science languages.

The talk, entitled “Detecting and Repairing Anti-Patterns in Asynchronous JavaScript,” was the keynote that kicked off a series of lightning talks by other graduate students. An abstract and photos from the event may be found below. Thank you, Alexi, for visiting CUNY!

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Talk at NEPLS at Harvard University

I gave a talk at the New England Programming Languages and Systems (NEPLS) symposium at Harvard University earlier this month.

Talk at University of Tokyo

On August 18, I visited Professor Shigeru Chiba at the Core Software Group of the Dept. of Creative Informatics Graduate School of Information Science and Technology at The University of Tokyo. I gave a talk about preliminary research in automated refactoring of Deep Learning software.

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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!

Preprint of ICSE ’21 ML systems study paper now available

A preprint of our ICSE ’21 paper on studying refactoring and technical debt in Machine Learning systems is now available.

Paper on refactorings and technical debt in Machine Learning systems accepted at ICSE 2021

Our paper entitled, “An empirical study of refactorings and technical debt in Machine Learning systems,” has been accepted to the main technical research track at the 2021 International Conference on Software Engineering (ICSE)! Out of 602 papers, 138 were accepted, amounting to a 23% acceptance rate. Congrats to Yiming, Mehdi, Rhia, Ajani, and Anita, and thank you for all of your hard work!

Journal extension accepted to Science of Computer Programming with minor revisions

A journal extension of our ICSE ’19 paper entitled, “Safe Automated Refactoring for Intelligent Parallelization of Java 8 Streams,” has been accepted with minor revisions to the Science of Computer Programming journal.