Efficient random forest algorithm for multi-objective optimization in software defect prediction

S Kanwar, LK Awasthi, V Shrivastava - IETE Journal of Research, 2023 - Taylor & Francis
The Software Defect Prediction (SDP) process provides reliable software by identifying
defect-prone modules before the testing stage. It efficiently and effectively utilizes quality …

[PDF][PDF] Peningkatan Akurasi Prediksi Waktu Perbaikan Bug dengan Pendekatan Partisi Data

MA Ridwan, S Rochimah - JSINBIS (Jurnal Sistem Informasi Bisnis …, 2018 - researchgate.net
Pengembang perangkat lunak perlu memiliki rencana dalam pengaturan biaya
pengembangan perangkat lunak. Perbaikan perangkat lunak dalam fase pemeliharaan …

Pengujian Dan Penerapan Manajemen Kas RW Dengan Metode Black Box

H Hardianto, FP Hardianti, RR Irawan… - J-SAKTI (Jurnal …, 2024 - tunasbangsa.ac.id
Pengujian perangkat lunak adalah bagian penting dari pengembangan aplikasi untuk
memastikan kualitas dan keandalannya. Penelitian ini menggunakan metode Black Box …

Implementation of chaotic gaussian particle swarm optimization for optimize learning-to-rank software defect prediction model construction

MA Buchari, S Mardiyanto… - Journal of Physics …, 2018 - iopscience.iop.org
Finding the existence of software defect as early as possible is the purpose of research
about software defect prediction. Software defect prediction activity is required to not only …

[引用][C] Implementasi Iso 25010: 2010 Untuk Evaluasi Kualitas Perangkat Lunak (Studi Kasus: I-Gracias Universitas Telkom)

R Maliki, K Wiharja, KA Laksitowening - Universitas Telkom, 2014

Software defect prediction using SMOTE and artificial neural network

WA Dipa, WD Sunindyo - 2021 International Conference on …, 2021 - ieeexplore.ieee.org
defect prediction (SDP) is process of identifying software defect on the early testing stage of
SDLC. SDP can saving time software tester on the development process. There are some …

Analysis of feature ranking techniques for defect prediction in software systems

S Sabharwal, S Nagpal, N Malhotra, P Singh… - Quality, IT and Business …, 2018 - Springer
Software quality is an important parameter, and it plays a crucial role in software
development. One of the most important software quality attributes is fault proneness. It …

Comparative Analysis of Random Forests with Statistical and Machine Learning Methods in Predicting Fault-Prone Classes

R Malhotra, A Kaur, Y Singh - Cross-Disciplinary Applications of …, 2012 - igi-global.com
There are available metrics for predicting fault prone classes, which may help software
organizations for planning and performing testing activities. This may be possible due to …

[PDF][PDF] Software Defect Prediction Analysis Using Machine Learning Techniques. Sustainability 2023, 15, 5517

A Khalid, G Badshah, N Ayub, M Shiraz, M Ghouse - 2023 - academia.edu
There is always a desire for defect-free software in order to maintain software quality for
customer satisfaction and to save testing expenses. As a result, we examined various known …

[PDF][PDF] Implementation of Data Level Approach Techniques to Solve Unbalanced Data Case on Software Defect Classification

H Rahardian, MR Faisal… - Journal of …, 2020 - download.garuda.kemdikbud.go.id
Defects can cause significant software rework, delays, and high costs, to prevent disability it
must be predictable the possibility of defects. To predict the disability the metrics software …