Reinforcement learning for android gui testing

D Adamo, MK Khan, S Koppula, R Bryce - Proceedings of the 9th ACM …, 2018 - dl.acm.org
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 …

BIM-based smart safety monitoring system using a mobile app: a case study in an ongoing construction site

MM Hossain, S Ahmed, SMA Anam… - Construction …, 2023 - emerald.com
Purpose Construction safety is a crucial aspect that has far-reaching impacts on economic
development. But safety monitoring is often reliant on labor-based observations, which can …

The role of model checking in software engineering

AK Karna, Y Chen, H Yu, H Zhong, J Zhao - Frontiers of Computer Science, 2018 - Springer
Abstract Model checking is a formal verification technique. It takes an exhaustively strategy
to check hardware circuits and network protocols against desired properties. Having been …

Android gui test generation with sarsa

MK Khan, R Bryce - 2022 IEEE 12th Annual Computing and …, 2022 - ieeexplore.ieee.org
Android applications are often challenging to test because of large event spaces with an
exponential number of event sequences. Several studies employ reinforcement learning to …

The investigation of TLC model checker properties

VV Shkarupylo, I Tomičić, KM Kasian - Journal of Information and …, 2016 - hrcak.srce.hr
Sažetak This paper presents the investigation and comparison of TLC model checking
method (TLA Checker) properties. There are two different approaches to method usage …

Validation of the Hybrid ERTMS/ETCS Level 3 using Spin

P Arcaini, J Kofroň, P Ježek - International Journal on Software Tools for …, 2020 - Springer
Abstract The Hybrid ERTMS/ETCS Level 3 is a standard for the management and
interoperation of signalling for railways by the European Union. Its aim was to increase the …

Performance Analysis of Spotify® for Android with Model‐Based Testing

AR Espada, MM Gallardo, A Salmerón… - Mobile Information …, 2017 - Wiley Online Library
This paper presents the foundations and the real use of a tool to automatically detect
anomalies in Internet traffic produced by mobile applications. In particular, our MVE tool is …

A deep reinforcement learning-based approach for android gui testing

Y Gao, C Tao, H Guo, J Gao - Asia-Pacific Web (APWeb) and Web-Age …, 2022 - Springer
The mobile application market is booming, and Android applications occupy a vast market
share. However, the applications may contain many errors. The task in the testing phase is …

Post prioritization techniques to improve code coverage for sarsa generated test cases

MK Khan, R Michaels, D Williams… - 2023 IEEE 13th …, 2023 - ieeexplore.ieee.org
Reinforcement learning techniques are gaining popularity for automated test suite
generation. SARSA (State-Action-Reward-State-Action) is one such reinforcement learning …

Runtime verification of expected energy consumption in smartphones

AR Espada, M del Mar Gallardo, A Salmerón… - … SPIN Workshop on …, 2015 - Springer
Smartphones connected to Internet should work properly for days without a reset. One of the
most critical non-functional properties to ensure the correct behavior is energy consumption …