With software's increasing scale and complexity, software failure is inevitable. To date,
although many kinds of software fault localization methods have been proposed and have …

Software failure is inevitable with the increase in scale and complexity of the software.
Existing fault localization techniques based on neural networks take statement coverage …

In this article, we propose a hierarchical fault localization technique using a deep neural
network (DNN). First, we prioritize the functions of a program based on their suspiciousness …

Many fault localization approaches recently utilize deep learning to learn an effective
localization model showing a fresh perspective with promising results. However, localization …

Context: The recent progress of deep learning has shown its promising learning ability in
making sense of data, and many fields have utilized this learning ability to learn an effective …

Many learning based fault localization approaches haven been proposed to improve the
effectiveness by fusing various dimension of fault diagnosis features. However, method calls …

Context Automatic software fault localization serves as a significant purpose in helping
developers solve bugs efficiently. Existing approaches for software fault localization can be …

Effective debugging is necessary for producing high quality and reliable software. Fault
localization plays a vital role in the debugging process. However, fault localization is the …

We propose the application of a modified radial basis function neural network in the context
of software fault localization, to assist programmers in locating bugs effectively. This neural …

Fault localization aims at identifying suspicious statements potentially responsible for
failures. The recent rapid progress on deep learning shows the promising potential of many …