Context: User stories have been widely accepted as artifacts to capture the user
requirements in agile software development. They are short pieces of texts in a semi …

App reviews found in app stores can provide critically valuable information to help software
engineers understand user requirements and to design, debug, and evolve software …

We propose a network for Congested Scene Recognition called CSRNet to provide a data-
driven and deep learning method that can understand highly congested scenes and perform …

Machine learning (ML) is used increasingly in real-world applications. In this paper, we
describe our ongoing endeavor to define characteristics and challenges unique to …

The role of sentiment analysis is increasingly emerging to study software developers'
emotions by mining crowd-generated content within software repositories and information …

In this paper, we take up the second RE17 data challenge: the identification of requirements
types using the" Quality attributes (NFR)" dataset provided. We studied how accurately we …

Opinion mining, sometimes referred to as sentiment analysis, has gained increasing
attention in software engineering (SE) studies. SE researchers have applied opinion mining …

Context: Requirements engineering (RE) researchers have been experimenting with
machine learning (ML) and deep learning (DL) approaches for a range of RE tasks, such as …

App stores include an increasing amount of user feedback in form of app ratings and
reviews. Research and recently also tool vendors have proposed analytics and data mining …

Requirements engineering has traditionally been stakeholder-driven. In addition to domain
knowledge, widespread digitalization has led to the generation of vast amounts of data (Big …