As query reformulation is tedious for developers, especially for novices, we propose an automated software-specific query reformulation approach based on deep learning.
Graphical User Interface (GUI) is ubiquitous in almost all modern desktop software, mobile applications, and online websites.
The core of the attack is a neural conditional branch constructed with a trigger detector and several operators and injected into the victim model as a malicious payload.
Deep learning has shown its power in many applications, including object detection in images, natural-language understanding, and speech recognition.
We conduct the first large-scale empirical study of seven representative GUI element detection methods on over 50k GUI images to understand the capabilities, limitations and effective designs of these methods.
However, the prerequisite of using screen readers is that developers have to add natural-language labels to the image-based components when they are developing the app.
Deep learning (DL) defines a new data-driven programming paradigm that constructs the internal system logic of a crafted neuron network through a set of training data.