SPLASH 2020
Sun 15 - Sat 21 November 2020 Online Conference
Tue 17 Nov 2020 12:20 - 13:00 at SPLASH-I - Breakfast in Wellington
Wed 18 Nov 2020 00:20 - 01:00 at SPLASH-I - Breakfast in Paris

Tue 17 Nov

Displayed time zone: Central Time (US & Canada) change

12:20 - 13:00
Breakfast in WellingtonStudent Research Competition at SPLASH-I +12h
  • Aidan Yang, SOAR: Synthesis for Open-Source API Refactoring

  • Gahwon Lee, SASIL: A Domain-Specific Language for Simulating Declarative Specifications of Scheduling Systems

  • Ian C. McCormack, A Software Library Model for the Internet of Things

  • Mona Zhang and Jacob Gorenburg, Design and Implementation of a Gradual Verifier

  • Raphael Mosaner, Machine Learning to Ease Understanding of Data Driven Compiler Optimizations

  • Reed Oei, Psamathe: A DSL for Safe Blockchain Assets

  • Sang Heon Choi, Consolidation: A Technique for Improving Permissiveness of Human-Machine Interfaces

  • Sophia Kolak, Detecting Performance Patterns with Deep Learning

  • Vitaly Romanov, Evaluating Importance of Edge Types when Using Graph Neural Network for Predicting Return Types of Python Functions

12:20
40m
Poster
Student Research Competition
Student Research Competition

Wed 18 Nov

Displayed time zone: Central Time (US & Canada) change

00:20 - 01:00
Breakfast in ParisStudent Research Competition at SPLASH-I
  • Aidan Yang, SOAR: Synthesis for Open-Source API Refactoring

  • Gahwon Lee, SASIL: A Domain-Specific Language for Simulating Declarative Specifications of Scheduling Systems

  • Ian C. McCormack, A Software Library Model for the Internet of Things

  • Mona Zhang and Jacob Gorenburg, Design and Implementation of a Gradual Verifier

  • Raphael Mosaner, Machine Learning to Ease Understanding of Data Driven Compiler Optimizations

  • Reed Oei, Psamathe: A DSL for Safe Blockchain Assets

  • Sang Heon Choi, Consolidation: A Technique for Improving Permissiveness of Human-Machine Interfaces

  • Sophia Kolak, Detecting Performance Patterns with Deep Learning

  • Vitaly Romanov, Evaluating Importance of Edge Types when Using Graph Neural Network for Predicting Return Types of Python Functions

00:20
40m
Poster
Student Research Competition
Student Research Competition