A stochastic process of software fault detection and correction for business operations
DS Kumar, AS Rao, NM Kumar, N Jeebaratnam… - The Journal of High …, 2023 - Elsevier
Automatic software fault detection and repair is made possible by autonomic software
recovery. By incorporating this function, the software will run more efficiently and …
recovery. By incorporating this function, the software will run more efficiently and …
[HTML][HTML] Automatic software bug prediction using adaptive golden eagle optimizer with deep learning
In the software maintenance and development process, the software bug detection is an
essential problem because it related with the complete software successes. So, the earlier …
essential problem because it related with the complete software successes. So, the earlier …
[PDF][PDF] Peningkatan Kinerja Prediksi Cacat Software dengan Hyperparameter Tuning pada Algoritma Klasifikasi Deep Forest
PENINGKATAN KINERJA PREDIKSI CACAT SOFTWARE DENGAN HYPERPARAMETER
TUNING PADA ALGORITMA KLASIFIKASI DEEP FOREST Page 1 Jurnal MNEMONIC Vol 5 …
TUNING PADA ALGORITMA KLASIFIKASI DEEP FOREST Page 1 Jurnal MNEMONIC Vol 5 …
[PDF][PDF] Liver ailment prediction using random forest model
Today, liver disease, or any deterioration in one's ability to survive, is extremely common all
around the world. Previous research has indicated that liver disease is more frequent in …
around the world. Previous research has indicated that liver disease is more frequent in …
[PDF][PDF] Abmj: An ensemble model for risk prediction in software requirements
MM Otoom - Ijcsns, 2022 - researchgate.net
Due to the rising complexity of software projects, it is quite difficult to predict the risk in
software requirements which is the most profound and essential activity in SDLC. It may lead …
software requirements which is the most profound and essential activity in SDLC. It may lead …
[PDF][PDF] Comparing the accuracy and developed models for predicting the confrontation naming of the elderly in South Korea using weighted random forest, random …
H Byeon - International Journal of Advanced Computer Science …, 2021 - researchgate.net
Since dementia patients clearly show the retrogression of linguistic ability from the early
stage, evaluating cognitive and language abilities is very important when diagnosing …
stage, evaluating cognitive and language abilities is very important when diagnosing …
Software Defect Prediction: A Comparative Analysis of Machine Learning Techniques
The early prediction of defective modules in developing software can help the development
team to utilize the available resources efficiently to deliver high quality software product in …
team to utilize the available resources efficiently to deliver high quality software product in …
Improving the accuracy of text classification using the over sampling technique in the case of sinovac vaccine
The WHO has declared COVID-19 (Coronavirus Disease 2019) a global health emergency.
Up to 19 November 2021, the total positive cases in Indonesia reached 4,252,705, of which …
Up to 19 November 2021, the total positive cases in Indonesia reached 4,252,705, of which …
Correlation-based modified long short-term memory network approach for software defect prediction
Developing software applications has become more perplexing nowadays due to the huge
usage of software applications. Under such circumstances, developing software without …
usage of software applications. Under such circumstances, developing software without …
[HTML][HTML] Enhancing software defect prediction: a framework with improved feature selection and ensemble machine learning
M Ali, T Mazhar, A Al-Rasheed, T Shahzad… - PeerJ Computer …, 2024 - peerj.com
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 …
enabling the identification of defective modules before the testing phase. This study aims to …