LCNN: Lightweight CNN architecture for software defect feature identification using Explainable AI
Software defect identification (SDI) is a key part of improving the quality of software projects
and lowering the risks that along with maintenance. It does identify the software defect …
and lowering the risks that along with maintenance. It does identify the software defect …
IMDAC: A robust intelligent software defect prediction model via multi‐objective optimization and end‐to‐end hybrid deep learning networks
K Zhu, N Zhang, C Jiang, D Zhu - Software: Practice and …, 2024 - Wiley Online Library
Software defect prediction (SDP) aims to build an effective prediction model for historical
defect data from software repositories by some specialized techniques or algorithms, and …
defect data from software repositories by some specialized techniques or algorithms, and …
Software Defects Identification: Results Using Machine Learning and Explainable Artificial Intelligence Techniques
The rising deployment of software in automation and the cognitive skills of machines
indicate a machine revolution in modern human civilization. Thus, diagnosing and predicting …
indicate a machine revolution in modern human civilization. Thus, diagnosing and predicting …
Software defect prediction based on deep learning models: Performance study
In recent years, defect prediction, one of the major software engineering problems, has been
in the focus of researchers since it has a pivotal role in estimating software errors and faulty …
in the focus of researchers since it has a pivotal role in estimating software errors and faulty …
Hybrid Defect Prediction Model Based on Counterfactual Feature Optimization
W Zheng, TF Chen, MT Hu, FY Yang, X Fan… - Human-Centric Intelligent …, 2023 - Springer
Software defect prediction is critical to ensuring software quality. Researchers have worked
on building various defect prediction models to improve the performance of defect …
on building various defect prediction models to improve the performance of defect …
An improved cnn-based architecture for within-project software defect prediction
R Malohtra, HS Yadav - … Computing and Signal Processing: Proceedings of …, 2021 - Springer
To improve the software quality, the software is generally tested to find out any bugs or a
simple reliability test. A reliable software defect checking mechanism is a leading research …
simple reliability test. A reliable software defect checking mechanism is a leading research …
Semantic and traditional feature fusion for software defect prediction using hybrid deep learning model
Software defect prediction aims to find a reliable method for predicting defects in a particular
software project and assisting software engineers in allocating limited resources to release …
software project and assisting software engineers in allocating limited resources to release …
Software defect-based prediction using logistic regression: Review and challenges
J Goyal, R Ranjan Sinha - Second International Conference on …, 2022 - Springer
Software analysis and prediction system development is the significant and much-needed
field of software testing in software engineering. The automatic software predictors analyze …
field of software testing in software engineering. The automatic software predictors analyze …
Deep learning-based software defect prediction via semantic key features of source code—systematic survey
Software defect prediction (SDP) methodology could enhance software's reliability through
predicting any suspicious defects in its source code. However, developing defect prediction …
predicting any suspicious defects in its source code. However, developing defect prediction …
A deep introduction to ai based software defect prediction (SDP) and its current challenges
MBR Pandit, N Varma - TENCON 2019-2019 IEEE Region 10 …, 2019 - ieeexplore.ieee.org
Software systems are driving the quality of human life. Annual investment in software
systems development is exceeding 4 trillion USD. Given the increasing complexity of …
systems development is exceeding 4 trillion USD. Given the increasing complexity of …