Mon 5 Nov 2018 10:30 - 10:48 at Sandy Lake - A-TEST II

This paper presents a reinforcement learning approach to automated GUI testing of Android apps. We use a test generation algorithm based on Q-learning to systematically select events and explore the GUI of an application under test without requiring a preexisting abstract model. We empirically evaluate the algorithm on eight Android applications and find that the proposed approach generates test suites that achieve between 3.31% to 18.83% better block-level code coverage than random test generation.

Mon 5 Nov

Displayed time zone: Guadalajara, Mexico City, Monterrey change

10:30 - 12:00
A-TEST IIA-TEST at Sandy Lake
10:30
18m
Talk
Reinforcement Learning for Android GUI Testing
A-TEST
David Adamo Ultimate Software, USA, Md Khorrom Khan University of North Texas, USA, Sreedevi Koppula University of North Texas, USA, Renée Bryce University of North Texas, USA
10:48
18m
Talk
Extending Equivalence Transformation Based Program Generator for Random Testing of C Compilers
A-TEST
Shogo Takakura Kwansei Gakuin University, Japan, Mitsuyoshi Iwatsuji Kwansei Gakuin University, Japan, Nagisa Ishiura Kwansei Gakuin University
11:06
18m
Talk
HDDr: A Recursive Variant of the Hierarchical Delta Debugging Algorithm
A-TEST
Ákos Kiss University of Szeged, Hungary, Renáta Hodován University of Szeged, Hungary, Tibor Gyimóthy University of Szeged, Hungary
11:24
18m
Talk
Goal-Oriented Mutation Testing with Focal Methods
A-TEST
Sten Vercammen University of Antwerp, Belgium, Mohammad Ghafari University of Bern, Serge Demeyer University of Antwerp, Belgium, Markus Borg RISE Research Institutes of Sweden AB
Pre-print
11:42
18m
Talk
A Reinforcement Learning Based Approach to Automated Testing of Android Applications
A-TEST
Thi Anh Tuyet Vuong Keio University, Japan, Shingo Takada Keio University, Japan