Software development involves plenty of risks, and errors exist in software modules
represent a major kind of risk. Software defect prediction techniques and tools that identify …

Identifying/removing software defects is time consuming. In ill planned projects, rectifying
defects consumes more time than for code development. Defective module prediction is …

A recent study namely software defect prediction model based on Local Linear Embedding
and Support Vector Machines (LLE-SVM) has indicated that Support Vector Regression …

In software testing, automatic detection of faults and defects in software is both complex and
important. There are different techniques utilized to predict future defects. Machine learning …

Software failure such as software defect causes billion of dollar loss every year. Software
failure also affects billion of people worldwide. Inadequate software testing can cause …

In this paper, we study the learning impact of data sampling followed by attribute selection
on the classification models built with binary class imbalanced data within the scenario of …

The purpose of software defect prediction is to improve the quality of a software project by
building a predictive model to decide whether a software module is or is not fault prone. In …

Machine learning techniques are frequent for the complicated task of predicting software
defects. Often the prediction models fail to predict defects successfully as the between class …

Accurate prediction of fault-prone modules in software development process enables
effective discovery and identification of the defects. Such prediction models are especially …

Defect prediction in software projects plays a crucial role to reduce quality-based risk and
increase the capability of detecting faulty program modules. Hence, classification …