Context: Automated software defect prediction (SDP) methods are increasingly applied,
often with the use of machine learning (ML) techniques. Yet, the existing ML-based …

In software engineering community, defect prediction is one the active domain. For the
software's success, it is essential to reduce the software engineering and data-mining gap …

At the end of 2019, the world was hit by the COVID-19 virus, which caused a pandemic.
Indonesia has become one of the countries that are affected by this pandemic. To control the …

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 …

Perkembangan digital dapat meringankan aktivitas manusia dalam menggunakan, serta
mengelola informasi. Suatu informasi berdasarkan kumpulan data dengan dilakukannya …

Software defect prediction enhances the quality, efficiency, and effectiveness of time and
expenses for software testing by focusing on defect modules. Software defect prediction …

At the latest, a lot of studies have been conducted to forecast software flaws and determine if
modules are defective or not, in order to build high-quality software at a low cost before …

The cost of software testing could be reduced if faulty entities were identified prior to the
testing phase, which is possible with software fault prediction (SFP). In most SFP models …

Testing of software ensures the supply of meaningful software and hence prediction of
defects in producing high quality software has become an inevitable one. Software defect …

Software defect prediction is an active research area. Researchers have proposed many
approaches to overcome the imbalanced defect problem and build highly effective machine …