The software engineering community is rapidly adopting machine learning for transitioning
modern-day software towards highly intelligent and self-learning systems. However, the …

Context: The software development industry is rapidly adopting machine learning for
transitioning modern day software systems towards highly intelligent and self-learning …

Since twenty-first century, software quality is considered as a vital factor in the global
competitive position for any software product in order to ensure quality and to ensure the …

In software development, triaging deals with activities that are involved in the management
of work items, ie, items that need to be completed in a given iteration/sprint. These activities …

Abstract In Software Development Life Cycle (SDLC), the coding plays the very crucial
phase so far as quality of software is concerned. The quality of software highly depends on …

This research was conducted to perform an in-depth analysis of the coupling metrics of 10
Open Source Software (OSS) projects obtained from the Comets dataset. More precisely, we …

The potential of AI to process and interpret large volumes of data can provide researchers
with a powerful tool to understand and monitor biodiversity on a global scale. In this paper …

A quality prediction mechanism has been developed in this paper. K-means clustering
algorithm has been applied for the clustering of object-oriented features. Finally logistic …

The need for computers increased quickly. As a result, the program is utilized in a significant
and intricate manner. More complex systems are being developed by software businesses …

Software fault/defect prediction aids software engineers in identifying defective
constructions, including classes and modules early in software development life cycle. Deep …