Effective software defect prediction is a crucial aspect of software quality assurance,
enabling the identification of defective modules before the testing phase. This study aims to …

Nowadays, in the topics related to prediction, in addition to increasing the accuracy of
existing algorithms, the reduction of computational time is a challenging issue that has …

Software defect prediction plays a crucial role in enhancing software quality while achieving
cost savings in testing. Its primary objective is to identify and send only defective modules to …

Concept drift (CD) refers to data distributions that may vary after a minimum stable period.
CD negatively influences models' performance of software defect prediction (SDP) trained …

Software Fault Forecasting (SFF) pertains to timely identifying sections in software projects
that are prone to faults and may result in significant development expenses. Deep learning …

Defects in software are one of the critical problems in software engineering community
because they provide inaccurate results and negatively affect the quality and reliability of the …

This paper presents an ensemble model for software defect prediction using methodlevel
features of a Spring Framework open-source Java project called Broadleaf Commerce. The …

Software Defect Prediction (SDP) predicts new defects through machine learning trained
with historical defect data. The distribution of software defects is highly unbalanced, which …

The correctness of software systems is vital for their effective operation. It makes discovering
and fixing software bugs an important development task. The increasing use of Artificial …

Software defect prediction is one of the essential sets of operation towards mitigating issues
of risk management in software development known to contribute towards enhancing the …