Software testing with large language models: Survey, landscape, and vision
Pre-trained large language models (LLMs) have recently emerged as a breakthrough
technology in natural language processing and artificial intelligence, with the ability to …
technology in natural language processing and artificial intelligence, with the ability to …
Mutation testing advances: an analysis and survey
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 …
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 …
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
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 …
many GUIs require appropriate text inputs to proceed to the next page, which remains a …
Superion: Grammar-aware greybox fuzzing
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 …
effective techniques for finding security bugs in practice. Particularly, American Fuzzy Lop …
Reinforcement learning based curiosity-driven testing of Android applications
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 …
to guarantee their correctness. Model-based and systematic approaches have been applied …
MODE: automated neural network model debugging via state differential analysis and input selection
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 …
Just like software inevitably has bugs, models have bugs too, leading to poor classification …
Wuji: Automatic online combat game testing using evolutionary deep reinforcement learning
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 …
relies on manual playing and scripting based testing in game industry. Even until recently …
From ui design image to gui skeleton: a neural machine translator to bootstrap mobile gui implementation
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 …
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
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 …
how to interact with it, in order to achieve high coverage with a limited time budget …