Software testing with large language models: Survey, landscape, and vision

J Wang, Y Huang, C Chen, Z Liu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Pre-trained large language models (LLMs) have recently emerged as a breakthrough
technology in natural language processing and artificial intelligence, with the ability to …

Mutation testing advances: an analysis and survey

M Papadakis, M Kintis, J Zhang, Y Jia, Y Le Traon… - Advances in …, 2019 - Elsevier
Mutation testing realizes the idea of using artificial defects to support testing activities.
Mutation is typically used as a way to evaluate the adequacy of test suites, to guide the …

A taxonomy of metrics for GUI-based testing research: A systematic literature review

R Coppola, E Alégroth - Information and Software Technology, 2022 - Elsevier
Context: GUI-based testing is a sub-field of software testing research that has emerged in
the last three decades. GUI-based testing techniques focus on verifying the functional …

Fill in the blank: Context-aware automated text input generation for mobile gui testing

Z Liu, C Chen, J Wang, X Che, Y Huang… - 2023 IEEE/ACM 45th …, 2023 - ieeexplore.ieee.org
Automated GUI testing is widely used to help ensure the quality of mobile apps. However,
many GUIs require appropriate text inputs to proceed to the next page, which remains a …

Superion: Grammar-aware greybox fuzzing

J Wang, B Chen, L Wei, Y Liu - 2019 IEEE/ACM 41st …, 2019 - ieeexplore.ieee.org
In recent years, coverage-based greybox fuzzing has proven itself to be one of the most
effective techniques for finding security bugs in practice. Particularly, American Fuzzy Lop …

Reinforcement learning based curiosity-driven testing of Android applications

M Pan, A Huang, G Wang, T Zhang, X Li - Proceedings of the 29th ACM …, 2020 - dl.acm.org
Mobile applications play an important role in our daily life, while it still remains a challenge
to guarantee their correctness. Model-based and systematic approaches have been applied …

Wuji: Automatic online combat game testing using evolutionary deep reinforcement learning

Y Zheng, X Xie, T Su, L Ma, J Hao… - 2019 34th IEEE/ACM …, 2019 - ieeexplore.ieee.org
Game testing has been long recognized as a notoriously challenging task, which mainly
relies on manual playing and scripting based testing in game industry. Even until recently …

MODE: automated neural network model debugging via state differential analysis and input selection

S Ma, Y Liu, WC Lee, X Zhang, A Grama - … of the 2018 26th ACM Joint …, 2018 - dl.acm.org
Artificial intelligence models are becoming an integral part of modern computing systems.
Just like software inevitably has bugs, models have bugs too, leading to poor classification …

From ui design image to gui skeleton: a neural machine translator to bootstrap mobile gui implementation

C Chen, T Su, G Meng, Z Xing, Y Liu - Proceedings of the 40th …, 2018 - dl.acm.org
A GUI skeleton is the starting point for implementing a UI design image. To obtain a GUI
skeleton from a UI design image, developers have to visually understand UI elements and …

Humanoid: A deep learning-based approach to automated black-box android app testing

Y Li, Z Yang, Y Guo, X Chen - 2019 34th IEEE/ACM …, 2019 - ieeexplore.ieee.org
Automated input generators must constantly choose which UI element to interact with and
how to interact with it, in order to achieve high coverage with a limited time budget …