Machine learning methods in software engineering are becoming increasingly important as
they can improve quality and testing efficiency by constructing models to predict defects in …

Context Software defect prediction (SDP) is an important task in software engineering. Along
with estimating the number of defects remaining in software systems and discovering defect …

Software defection prediction is not only crucial for improving software quality, but also
helpful for software test effort estimation. As is well-known, 80% of the fault happens in 20 …

Software is a complex entity composed in various modules with varied range of defect
occurrence possibility. Efficient and timely prediction of defect occurrence in software allows …

Machine Learning approaches are good in solving problems that have less information. In
most cases, the software domain problems characterize as a process of learning that …

In the arena of software engineering, software defects prediction is one of the most attractive
research topics. Here the main task is to predict if there is any bug in the software or not. For …

Software industry has stipulated the need for good quality software projects to be delivered
on time and within budget. Software defect prediction (SDP) has led to the application of …

Finding defects early in a software system is a crucial task, as it creates adequate time for
fixing such defects using available resources. Strategies such as symmetric testing have …

Several prediction approaches are contained in the arena of software engineering such as
prediction of effort, security, quality, fault, cost, and re-usability. All these prediction …

Software Defect Prediction (SDP) is an approach used for identifying defect-prone software
modules or components. It helps software engineer to optimally, allocate limited resources to …