BACKGROUND: Software quality prediction models play a crucial role in identifying
vulnerable software components during early stages of development, and thereby …

The prediction of software vulnerability requires crucial awareness during the software
specification, design, development, and configuration to achieve less vulnerable and secure …

Deep neural network models built by the appropriate design decisions are crucial to obtain
the desired classifier performance. This is especially desired when predicting fault …

Background: Machine learning techniques have been widely used and demonstrate
promising performance in many software security tasks such as software vulnerability …

Background: Prediction of software vulnerabilities is a major concern in the field of software
security. Many researchers have worked to construct various software vulnerability …

Software vulnerability provides the gateway for attackers to breach the confidentiality,
integrity, and availability of information systems. Therefore, the prediction of software …

The security of software has always been a vital concern for software developers.
Infringements on software systems can result in significant losses in terms of time and …

Background: Early identification of software vulnerabilities is an intrinsic step in achieving
software security. In the era of artificial intelligence, software vulnerability prediction models …

Hyperparameter optimization (HPO) is the procedure to find the optimal hyperparameters for
predictive modelling. In order to build an efficient software vulnerability prediction (SVP) …

Deep neural network models built by the appropriate design decisions are crucial to obtain
the desired classifier performance. is is especially desired when predicting fault proneness …