Recent years have seen a growing interest in deep learning-based approaches to localize
faults in software. However, existing methods have not reached a satisfying level of …

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

Deep learning-based fault localization has recently been widely studied. Previous studies
have demonstrated that deep learning-based methods can localize faults more accu-rately …

Fault localization is essential for solving the issue of software faults. Aiming at improving
fault localization, this paper proposes a deep learning-based fault localization with …

Numerous Deep Learning (DL)-based fault localization (FL) methods are developed with the
aim of leveraging the code coverage matrix and failure vector to identify the connection …

Existing fault localization based on neural networks utilize the information of whether a
statement is executed or not executed to identify suspicious statements potentially …

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 …

Automatic fault localization technology plays a critical role in software development by
automatically identifying potential faults in the code, thus helping programmers improve …

Software Fault Localization refers to the activity of finding code elements (eg, statements)
that are related to a software failure. The state-of-the-art fault localization techniques …

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 …