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Jul 6, 2018 15 tweets 41 min read Twitter logo Read on Twitter
@francesc @vadimlearning First #MLonCode paper presented by @vadimlearning is "code2vec: Learning Distributed Representations of Code" by Uri Alon, Meital Zilberstein, @omerlevy_, and @yahave.
@francesc @vadimlearning @omerlevy_ @yahave The second #MLonCode paper, also presented by @vadimlearning, is "A General Path-Based Representation for Predicting Program Properties" by ... wait for it ... Uri Alon, Meital Zilberstein, @omerlevy_, and @yahave 🎉
@francesc @vadimlearning @omerlevy_ @yahave Next, our #ML intern Romain Keramitas, is reviewing the #MLonCode paper "Mining Idioms from Source Code" by Miltiadis Allamanis and @RandomlyWalking
@francesc @vadimlearning @omerlevy_ @yahave @RandomlyWalking Up next, @kslavnov presents the #MLonCode paper "De-anonymizing Programmers via Code Stylometry" by Aylin Caliskan-Islam, Richard Harang, Andrew Liu, Arvind Narayanan, Clare Voss, Fabian Yamaguchi, and Rachel Greenstadt (this ones comes with a video!)
@francesc @vadimlearning @omerlevy_ @yahave @RandomlyWalking @kslavnov And now, the #MLonCode with probably the longest title ever "The Impact of IR-based Classifier Configuration on the Performance and the Effort of Method-Level Bug Localization"
@francesc @vadimlearning @omerlevy_ @yahave @RandomlyWalking @kslavnov And now @egor_bu reviews "Learning Natural Coding Conventions" by Miltiadis Allamanis, Earl T. Barr, @christianbird, and @RandomlyWalking

This is probably one my favorite #MLonCode papers, such a promising idea!
@francesc @vadimlearning @omerlevy_ @yahave @RandomlyWalking @kslavnov @egor_bu @christianbird And @egor_bu now continues the #MLonCode review meeting by talking about "Estimating defectiveness of source code: A predictive model using GitHub content" by Ritu Kapur and Balwinder Sodhi
@francesc @vadimlearning @omerlevy_ @yahave @RandomlyWalking @kslavnov @egor_bu @christianbird Now switching to bug prediction themed #MLonCode papers, @egor_bu is now reviewing "Entropy Guided Spectrum Based Bug Localization Using Statistical Language Model" by Saikat Chakraborty, Yujian Li, Matt Irvine, Ripon Saha, Baishakhi Ray
@francesc @vadimlearning @omerlevy_ @yahave @RandomlyWalking @kslavnov @egor_bu @christianbird And now Gabor Markowski, another one of our interns, presents remotely "Semantic Code Repair using Neuro-Symbolic Transformation Networks" by Jacob Devlin, Jonathan Uesato, Rishabh Singh, Pushmeet Kohli

#MLonCode #MachineLearning
@francesc @vadimlearning @omerlevy_ @yahave @RandomlyWalking @kslavnov @egor_bu @christianbird Next #MLonCode paper is "Automated software vulnerability detection with machine learning" by Jacob A. Harer et al.

The presenter is again our intern @Fulaphex presenting all the way from Poland 🇵🇱

#MachineLearning #MLonCode
@francesc @vadimlearning @omerlevy_ @yahave @RandomlyWalking @kslavnov @egor_bu @christianbird @Fulaphex And the third paper presented by @Fulaphex: "Syntax and Sensibility: Using language models to detect and correct syntax errors" by @_eddieantonio et al…

#MLonCode #MachineLearning
@francesc @vadimlearning @omerlevy_ @yahave @RandomlyWalking @kslavnov @egor_bu @christianbird @Fulaphex @_eddieantonio And we're down to three papers!

Up next @Fulaphex presents "Detecting API Documentation Errors" by @_zhong_hao and @zhendongsu from the Institute of Software at the Chinese Academy of Sciences…

#MLonCode #MachineLearning
@francesc @vadimlearning @omerlevy_ @yahave @RandomlyWalking @kslavnov @egor_bu @christianbird @Fulaphex @_eddieantonio @_Zhong_Hao @zhendongsu and to finish the #MLonCode review, our intern Romain Keramitas is back to the stage to present two papers:

"Deep Learning to Detect Redundant Method Comments" by Annie Louis et al from @edinburghnlp

#MLonCode #MachineLearning
@francesc @vadimlearning @omerlevy_ @yahave @RandomlyWalking @kslavnov @egor_bu @christianbird @Fulaphex @_eddieantonio @_Zhong_Hao @zhendongsu @EdinburghNLP and last but definitely not least, Romain presents "Deep Reinforcement Learning for Programming Language Correction" by Rahul Gupta, Aditya Kanade, Shirish Shevade

#MLonCode #MachineLearning
@francesc @vadimlearning @omerlevy_ @yahave @RandomlyWalking @kslavnov @egor_bu @christianbird @Fulaphex @_eddieantonio @_Zhong_Hao @zhendongsu @EdinburghNLP And with this we're done with #MLonCode review papers!
Up next a chat with the #ML team and all attendees.

Thanks everyone for joining, and thanks for the authors of all the papers ❤️

The video will be released soon.
Join the slack at to be notified.

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Jun 28, 2018
Today we're at #FOSD, talking about the future of software development with influential individuals in the fields of #MLonCode, #QuantumComputing, and #blockchain technologies.

Follow this thread for live tweeting!
Amazing talk by @KentBeck on how hundreds of thousands of developers could collaborate.

Moving from text transformations to tree transformations. Let's move away from "lines", which come from punch cards, and evolve into something that scales better.

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