Fuzz testing (fuzzing) has witnessed its prosperity in detecting security flaws recently. It
generates a large number of test cases and monitors the executions for defects. Fuzzing has …

In 2006, Geoffrey Hinton proposed the concept of training “Deep Neural Networks (DNNs)”
and an improved model training method to break the bottleneck of neural network …

Among the many software testing techniques available today, fuzzing has remained highly
popular due to its conceptual simplicity, its low barrier to deployment, and its vast amount of …

Natural language elements in source code, eg, the names of variables and functions,
convey useful information. However, most existing bug detection tools ignore this …

Mobile apps are ubiquitous, operate in complex environments and are developed under the
time-to-market pressure. Ensuring their correctness and reliability thus becomes an …

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 …

An increasingly popular set of techniques adopted by software engineering (SE)
researchers to automate development tasks are those rooted in the concept of Deep …

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 …

Mobile apps are indispensable for people's daily life, and automated GUI (Graphical User
Interface) testing is widely used for app quality assurance. There is a growing interest in …

For ensuring the reliability of Android apps, there has been tremendous, continuous
progress on improving automated GUI testing in the past decade. Specifically, dozens of …