The automatic localization of software faults plays a critical role in assisting software
professionals in fixing problems quickly. Despite various existing models for fault tolerance …

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

Considering the importance of software systems in human life, their quality assurance is very
important. Fault localization is one of the software testing steps, it tries to find the exact …

Accurate fault localization renders software test resource allocation and maintenance cost-
efficient. However, this is challenging when there are false alarm repercussions caused by …

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 …

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 …

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

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 …

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 …

Software Fault Forecasting (SFF) pertains to timely identifying sections in software projects
that are prone to faults and may result in significant development expenses. Deep learning …