Delivering high-quality software products is a challenging task. It needs proper coordination
from various teams in planning, execution, and testing. Many software products have high …

Software security vulnerabilities are one of the critical issues in the realm of computer
security. Due to their potential high severity impacts, many different approaches have been …

Data scarcity is a major challenge when training deep learning (DL) models. DL demands a
large amount of data to achieve exceptional performance. Unfortunately, many applications …

Recent advancements in technology have emerged the requirements of hardware and
software applications. Along with this technical growth, software industries also have faced …

Transfer learning aims to provide a framework to utilize previously-acquired knowledge to
solve new but similar problems much more quickly and effectively. In contrast to classical …

Defect prediction models help software quality assurance teams to allocate their limited
resources to the most defect-prone modules. Model validation techniques, such as-fold …

Software defect prediction is one of the most active research areas in software engineering.
We can build a prediction model with defect data collected from a software project and …

Background Software fault prediction is the process of developing models that can be used
by the software practitioners in the early phases of software development life cycle for …

Background: Cross project defect prediction (CPDP) recently gained considerable attention,
yet there are no systematic efforts to analyse existing empirical evidence. Objective: To …

Defect prediction models-classifiers that identify defect-prone software modules-have
configurable parameters that control their characteristics (eg, the number of trees in a …