Case study identification with GPT-4 and implications for mapping studies
Rainer and Wohlin showed that case studies are not well understood by reviewers and authors and thus they say that a given research is a case study when it is not.
Objective:Rainer and Wohlin proposed a smell indicator (inspired by ...
Understanding and evaluating software reuse costs and benefits from industrial cases—A systematic literature review
Software reuse costs and benefits have been investigated in several primary studies, which have been aggregated in multiple secondary studies as well. However, existing secondary studies on software reuse have not critically appraised ...
Architecting for sustainability of and in the cloud: A systematic literature review
The interest in the intersection between cloud computing and sustainability is naturally growing as the popularity of the former makes it in many cases the default model for delivering software functionalities to end users. Furthermore, ...
Graphical abstractDisplay Omitted
Highlights
- Infrequent utilization of Patterns and Tactics as reusable architectural solutions.
- Cloud computing as a context can affect the most addressed sustainability dimension.
- The environmental dimension is acknowledged as the foremost ...
The need for more informative defect prediction: A systematic literature review
Software defect prediction is crucial for prioritising quality assurance tasks, however, there are still limitations to the use of defect models. For example, the outputs often do not provide the defect type, severity, or the cause of ...
Knowledge and research mapping of the data and database forensics domains: A bibliometric analysis
The field of digital forensics has undergone rapid development alongside the technological advancements of the latest century. This study focuses in two of its subdomains, namely database forensics and data forensics. Though the concept of a ...
Technical risk model of machine learning based software project development - A multinational empirical study using modified Delphi-AHP method
The development of machine learning (ML) based software projects has increased significantly over the past decade, introducing new technical risks that rarely or never appear in traditional software development projects.
ObjectiveThis ...
Making vulnerability prediction more practical: Prediction, categorization, and localization
Due to the prevalence of software vulnerabilities, vulnerability detection becomes a fundamental problem in system security.
Objective:To solve this problem, academics and industries have made great efforts to propose deep-learning-...
A declarative approach to detecting design patterns from Java execution traces and source code
Design patterns are invaluable for software engineers because they help obtain well-structured and reusable object-oriented software components and contribute towards ease of software comprehension, maintenance, and modification. However, ...
Hybrid semantics-based vulnerability detection incorporating a Temporal Convolutional Network and Self-attention Mechanism
Desirable characteristics in vulnerability-detection (VD) systems (VDSs) include both good detection capability (high accuracy, low false positive rate, low false negative rate, etc.) and low time overheads. The widely used VDSs based on ...
Search-based co-creation of software models: The case of particle systems for video games
The video game industry is one of the fastest-growing industries in the world. However, the creation of content is the bottleneck of the industry nowadays.
Objective:In this paper, we propose a new approach for co-creating content by ...
Guiding the way: A systematic literature review on mentoring practices in open source software projects
Mentoring in Open Source Software (OSS) is important to its project’s growth and sustainability. Mentoring allows contributors to improve their technical skills and learn about the protocols and cultural norms of the project. However, ...
Not yet another BPM lifecycle: A synthesis of existing approaches using BPMN
Business Process Management (BPM) is considered an important management approach that encompasses a set of methods for managing the business processes of an organization. To maximize the benefits of BPM, scholars have conceptualized its ...
On the use of contextual information for machine learning based test case prioritization in continuous integration development
In most software organizations, Continuous Integration (CI) is a common practice usually subject to some budgets. Consequently, prioritizing test cases to be executed in the CI cycle is fundamental. The idea is first to execute test ...
Effective test generation using pre-trained Large Language Models and mutation testing
One of the critical phases in the software development life cycle is software testing. Testing helps with identifying potential bugs and reducing maintenance costs. The goal of automated test generation tools is to ease the development ...
Forward-Oriented Programming: A meta-DSL for fast development of component libraries
Libraries that implement Domain-Specific Language (DSL) components keep gaining traction when it comes to developing software for specific application domains. However, creating components that can be organically weaved into use cases is an ...
Quantum aided efficient resource control for connected support in IRS assisted networks
To achieve the vision of all connected world with uninterrupted communication support, 6G technology plays an important role. But the scarce radio spectrum and limited network resources is the main challenge in delivering its promised ...
Highlights
- An intelligent framework for 6G IoT network is proposed.
- IRS assists the AP-user node communication with NOMA beamforming.
- Quantum aided resource control algorithm is proposed.
- Average sum rate improves by 7.52% with proposed ...