October 5, 2018

Announcing the winners of the Facebook Testing and Verification research awards

By: Meta Research

We are pleased to announce the winners of the Facebook Testing and Verification Research Awards. Continued research and innovation is key to solve open scientific challenges. This research award opportunity looked for proposals that will lead to direct impact on the deployment and real world impact of Testing and Verification techniques in the technology sector.

Winners are invited to attend a one-day workshop co-located with the Facebook TAV Symposium, held at our London offices November 27th, 2018. The Facebook TAV Symposium has the goal to build meaningful collaboration and exchange between Testing and Verification scientific research and between academia and industry. This year’s Symposium will be held November 28-29, 2018. If you are interested in attending the Symposium, please register here.

The 10 Facebook Testing and Verification award winners and their topic areas are:

Incremental Verification, Gradually
Jonathan Aldrich (Carnegie Mellon University), Joshua Sunshine (Carnegie Mellon University), and Eric Tanter (Universidad de Chile)

Self-Adaptive Search for Sapienz
Thomas Vogel (Humboldt University of Berlin)

DIFFUZZ: Making Greybox Fuzz Testing Incremental
Koushik Sen (University of California – Berkeley)

Scalable and Intelligent UI Test Generation for Industrial Mobile Apps
Tao Xie (University of Illinois Urbana-Champaign)

High-Speed Automated Fixes
Jooyong Yi (Innopolis University)

Fix Detection in Infer by Quantitative Analysis
Axel Legay (University of Louvain-Belgium) and Fabrizio Bionndi (Inria)

An Incremental Approach for More Effective Testing
Sarfraz Khurshid (University of Texas – Austin)

Automated Accessibility Testing for Mobile Apps
Gordon Fraser (University Passau), Jose Miguel Rojas (University of Leicester) and Marcelo Medeiros Eler (University of Sao Paolo)

Improving Analysis via Automated Program Transformation
Claire Le Goues (Carnegie Mellon University)

Automated Software Migration Using Genetic Improvement
Justyna Petke (University College London)

We also awarded smaller feasibility study awards to enable promising researchers to develop their work further and to potentially submit to future phases. These winners and their topic areas are:

Randomized Testing for Randomized Programs
Justin Hsu (University of Wisconsin – Madison)

Compositional Abstractions for Verifying Concurrent Data Structures
Thomas Wies (New York University)

Learning Precise Quick Fixes from Open-Source Revision Histories
Loris D’Antoni (University of Wisconsin – Madison)

Efficient Concurrent Abstract Interpretation
Aditya Thakur (University of California – Davis)

Being Proactive in ATAFistic World
Darko Marinov (University of Illinois Urbana-Champaign)

A Markov Decision- Making Framework for All Tests are Flaky
Ladan Tahvildari (University of Waterloo)

Classifying Test Executions using Neural Networks
Ajitha Rajan (University of Edinburgh)