The selection of word embedding and deep learning models for better outcomes is vital.
Word embeddings are an n-dimensional distributed representation of a text that attempts to …

In 2006, Geoffrey Hinton proposed the concept of training “Deep Neural Networks (DNNs)”
and an improved model training method to break the bottleneck of neural network …

Deep Learning (DL) techniques for Natural Language Processing have been evolving
remarkably fast. Recently, the DL advances in language modeling, machine translation, and …

Since 2009, the deep learning revolution, which was triggered by the introduction of
ImageNet, has stimulated the synergy between Software Engineering (SE) and Machine …

With the development of blockchain technologies, many Ponzi schemes disguise
themselves under the veil of smart contracts. The Ponzi scheme contracts cause serious …

Given a bug report, bug localization technique can help developers automatically locate
potential buggy files. Information retrieval and deep learning approaches have been applied …

Bug reports facilitate software development teams in improving the quality of software.
These reports include significant information related to problems encountered within a …

Bug localization automatic localize relevant source files given a natural language
description of bug within a software project. For a large project containing hundreds and …

Text Retrieval (TR)-based approaches for bug localization rely on formulating an initial
query based on the full text of a bug report. When the query fails to retrieve the buggy code …

Context: Recently deep learning based Natural Language Processing (NLP) models have
shown great potential in the modeling of source code. However, a major limitation of these …