A systematic literature review of model-driven engineering using machine learning
Model-driven engineering (MDE) is a software engineering paradigm based on the
systematic use of models. Over the past few years, engineers have significantly increased …
systematic use of models. Over the past few years, engineers have significantly increased …
Development of method for identification the computer system state based on the decision tree with multi-dimensional nodes
SY Gavrylenko, VV Chelak… - … Computer Science, Control, 2022 - ric.zntu.edu.ua
Context. The problem of identifying the state of a computer system is considered. The object
of the research is the process of computer system state identification. The subject of the …
of the research is the process of computer system state identification. The subject of the …
“Will artificial intelligence platforms replace designers in the future?” analyzing the impact of artificial intelligence platforms on the engineering design industry through …
Y Li - Engineering Applications of Artificial Intelligence, 2024 - Elsevier
This research investigates the impact of artificial intelligence platforms on the engineering
design industry by analyzing the perceptions of color and views on artificial intelligence …
design industry by analyzing the perceptions of color and views on artificial intelligence …
A comprehensive MCDM-based approach for object-oriented metrics selection problems
Object-oriented programming (OOP) is prone to defects that negatively impact software
quality. Detecting defects early in the development process is crucial for ensuring high …
quality. Detecting defects early in the development process is crucial for ensuring high …
Automated detection of class diagram smells using self-supervised learning
Abstract Design smells are symptoms of poorly designed solutions that may result in several
maintenance issues. While various approaches, including traditional machine learning …
maintenance issues. While various approaches, including traditional machine learning …
Deep learning with class-level abstract syntax tree and code histories for detecting code modification requirements
OO Büyük, A Nizam - Journal of Systems and Software, 2023 - Elsevier
Improving code quality is one of the most significant issues in the software industry. Deep
learning is an emerging area of research for detecting code smells and addressing …
learning is an emerging area of research for detecting code smells and addressing …
Intelligent system to detect software defects in autonomous cars
Autonomous cars have become increasingly popular in the last decade because of their
numerous benefits, such as lower travel time, increased safety, and improved fuel economy …
numerous benefits, such as lower travel time, increased safety, and improved fuel economy …
[PDF][PDF] Insights of effectivity analysis of learning-based approaches towards software defect prediction.
D Rai, JA Prashant - International Journal of Electrical & …, 2024 - pdfs.semanticscholar.org
Software defect prediction is one of the essential sets of operation towards mitigating issues
of risk management in software development known to contribute towards enhancing the …
of risk management in software development known to contribute towards enhancing the …
[PDF][PDF] A proposed model for detecting defects in software projects
Defective modules that cause software execution failures are common in large software
projects. Source code for a significant number of modules may be found in several software …
projects. Source code for a significant number of modules may be found in several software …
Detecting Code Smell with a Deep Learning System
A Nizam, MY Avar, ÖK Adaş… - 2023 Innovations in …, 2023 - ieeexplore.ieee.org
Code smell detection is one of the most significant issues in the software industry. Metric-
based static code analysis tools are used to detect undesirable coding practices known as …
based static code analysis tools are used to detect undesirable coding practices known as …