Large language models for software engineering: A systematic literature review
Large Language Models (LLMs) have significantly impacted numerous domains, including
Software Engineering (SE). Many recent publications have explored LLMs applied to …
Software Engineering (SE). Many recent publications have explored LLMs applied to …
[HTML][HTML] A review of machine learning algorithms for identification and classification of non-functional requirements
M Binkhonain, L Zhao - Expert Systems with Applications: X, 2019 - Elsevier
Context Recent developments in requirements engineering (RE) methods have seen a
surge in using machine-learning (ML) algorithms to solve some difficult RE problems. One …
surge in using machine-learning (ML) algorithms to solve some difficult RE problems. One …
Norbert: Transfer learning for requirements classification
Classifying requirements is crucial for automatically handling natural language
requirements. The performance of existing automatic classification approaches diminishes …
requirements. The performance of existing automatic classification approaches diminishes …
[HTML][HTML] Zero-shot learning for requirements classification: An exploratory study
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 …
machine learning (ML) and deep learning (DL) approaches for a range of RE tasks, such as …
Eliciting security requirements and tracing them to design: an integration of Common Criteria, heuristics, and UMLsec
Building secure systems is difficult for many reasons. This paper deals with two of the main
challenges:(i) the lack of security expertise in development teams and (ii) the inadequacy of …
challenges:(i) the lack of security expertise in development teams and (ii) the inadequacy of …
Automatic requirements classification based on graph attention network
G Li, C Zheng, M Li, H Wang - IEEE Access, 2022 - ieeexplore.ieee.org
Requirements classification is a significant task for requirements engineering, which is time-
consuming and challenging. The traditional requirements classification models usually rely …
consuming and challenging. The traditional requirements classification models usually rely …
A deep learning framework for non-functional requirement classification
Analyzing, identifying, and classifying nonfunctional requirements from requirement
documents is time-consuming and challenging. Machine learning-based approaches have …
documents is time-consuming and challenging. Machine learning-based approaches have …
Machine learning in requirements elicitation: A literature review
A growing trend in requirements elicitation is the use of machine learning (ML) techniques to
automate the cumbersome requirement handling process. This literature review summarizes …
automate the cumbersome requirement handling process. This literature review summarizes …
An ensemble machine learning technique for functional requirement classification
In Requirement Engineering, software requirements are classified into two main categories:
Functional Requirement (FR) and Non-Functional Requirement (NFR). FR describes user …
Functional Requirement (FR) and Non-Functional Requirement (NFR). FR describes user …
Cataloging github repositories
GitHub is one of the largest and most popular repository hosting service today, having about
14 million users and more than 54 million repositories as of March 2017. This makes it an …
14 million users and more than 54 million repositories as of March 2017. This makes it an …