Brussels / 2 & 3 February 2019

schedule

ML on Code devroom


09 10 11 12 13 14 15 16 17 18
Sunday Understanding Source Code with Deep Learning Suggesting Fixes during Code Review with ML Astor: An automated software repair framework Code anomalies in Kotlin programs
Automatic detection of anomalous code fragments written in Kotlin
Predicting areas for PR Comments based on Code Vectors & Mailing List Data Deduplication on large amounts of code
Fuzzy deduplication of PGA using source{d} stack
How to build an automatic refactoring and migration toolkit Mining Source Code^3
Mining Idioms, Usages and Edits
Coming: a Tool for Mining Change Pattern Instances from Git Commits Neural commit message suggester
Proposing better git commit messages with neural networks
Smelling Source Code Using Deep Learning
Event Speakers Start End

Sunday

  Understanding Source Code with Deep Learning Miltos Allamanis 09:10 09:50
  Suggesting Fixes during Code Review with ML Vadim Markovtsev 09:50 10:30
  Astor: An automated software repair framework Matias Martinez 10:30 11:10
  Code anomalies in Kotlin programs
Automatic detection of anomalous code fragments written in Kotlin
Timofey Bryksin 11:10 11:50
  Predicting areas for PR Comments based on Code Vectors & Mailing List Data Holden Karau 11:50 12:30
  Deduplication on large amounts of code
Fuzzy deduplication of PGA using source{d} stack
Romain Keramitas 12:30 13:10
  How to build an automatic refactoring and migration toolkit Juliette Tisseyre 13:10 13:50
  Mining Source Code^3
Mining Idioms, Usages and Edits
Dario Di Nucci 13:50 14:30
  Coming: a Tool for Mining Change Pattern Instances from Git Commits Matias Martinez 14:30 15:10
  Neural commit message suggester
Proposing better git commit messages with neural networks
Alberto Massidda 15:10 15:50
  Smelling Source Code Using Deep Learning Tushar Sharma 15:50 16:30