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 …

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 …

Automated fault localization (FL) techniques collect runtime information as input data and
then analyze input data to identify the relationship between program statements and failures …

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 …

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 …

Software debugging is complex and challenging task for developers and testers. To
increase the active debugging performance, several fault localization techniques have been …

Fault localization (FL) is an essential phase in software debugging and is used to detect the
possible faulty location. Nowadays, deep learning technique has a great advantage to …

Automated fault localization has been extensively studied to improve the effectiveness of
software debugging. Existing automated fault localization methods neglect the guidance of …

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 …