Results 81 to 90 of about 198,133 (331)

Cross-Project Online Just-In-Time Software Defect Prediction

IEEE Transactions on Software Engineering, 2023
Cross-Project (CP) Just-In-Time Software Defect Prediction (JIT-SDP) makes use of CP data to overcome the lack of data necessary to train well performing JIT-SDP classifiers at the beginning of software projects.
Sadia Tabassum, Leandro L. Minku, Danyi Feng   +2 more
semanticscholar   +1 more source

Loss of IGF‐1R impairs DNA‐PKcs recruitment to chromatin leading to defective end‐joining

Molecular Oncology, EarlyView.
IGF‐1R promotes radioresistance by facilitating DNA‐PKcs recruitment to chromatin, enabling non‐homologous end‐joining (NHEJ) repair of double‐strand breaks. Inhibition or loss of IGF‐1R disrupts this recruitment to damage sites, driving compensatory reliance on microhomology‐mediated end‐joining (MMEJ) repair.
Matthew O. Ellis, Jack V. Mills, Wojciech Niedzwiedz, Valentine M. Macaulay   +3 more
wiley   +1 more source

SOFTWARE DEFECT PREDICTION TECHNIQUES IN SOFTWARE ENGINEERING: A REVIEW

, 2022
Defect prediction is one of the significant challenges in the software development lifecycle for improving software quality and reducing program testing time and cost.
MUNEER A. S. HAZZA, AHMED A. ABDU, MONEER A. S. HAZZA, MIJAHED ALJOBER, ADEL A. NASSER, HAKIM A. ABDU, ABDUALMAJED A. G. AL-KHULAIDI   +6 more
core   +1 more source

Finding novel vulnerabilities of hypomorphic BRCA1 alleles

Molecular Oncology, EarlyView.
Synthetic lethality screens performed to identify novel vulnerabilities often model complete gene loss, thereby overlooking patient‐derived hypomorphic mutations. In this study, we have performed genome‐wide CRISPR screens on BRCA1 hypomorphic mutations, showing BRCA1I26A behaves like wild‐type, while BRCA1R1699Q mimics deficiency. Furthermore, we have
Anne Schreuder, Klaas de Lint, Hồ Mỹ Phúc Võ, Mariana M. Góis, Rosalie A. Kampen, Marta San Martin Alonso, Ilse Nootenboom, Veronica Garzero, Tiemen J. Wendel, Rob M. F. Wolthuis, Sylvie M. Noordermeer   +10 more
wiley   +1 more source

Comparative Study of Various Hyperparameter Tuning on Random Forest Classification With SMOTE and Feature Selection Using Genetic Algorithm in Software Defect Prediction

Journal of Electronics Electromedical Engineering and Medical Informatics
Software defect prediction is necessary for desktop and mobile applications. Random Forest defect prediction performance can be significantly increased with the parameter optimization process compared to the default parameter.
Mulia Kevin Suryadi, R. Herteno, Setyo Wahyu Saputro, M. Faisal, Radityo Adi Nugroho   +4 more
semanticscholar   +1 more source

Defect patterns and structural properties in a mature well-specified software system [PDF]

, 2008
Software engineering is not an empirically based discipline. As a result, many of its practices are based on little more than a generally agreed feeling that something may be true.
Hopkins, Tim, Hatton, Leslie
core  

Deep Learning for Software Defect Prediction: An LSTM-based Approach

, 2023
Software defect prediction is an important aspect of software development, as it helps developers and organizations to identify and resolve bugs in the software before they become major issues.
Prashant Sahatiya, et al.
core   +1 more source

Developmental and Epileptic Encephalopathy due to Biallelic Pathogenic Variants in PIGM

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective PIGM encodes a critical enzyme in the glycosylphosphatidylinositol (GPI)‐anchor biosynthesis pathway. While promoter‐region mutations in PIGM have been associated with a relatively mild phenotype characterized by portal vein thrombosis and absence seizures, recent evidence suggests that coding‐region mutations result in a more severe
Júlia Sala‐Coromina, Anna Marcé‐Grau, Barbara Masotto, Marta Codina, Lamia BenJemaa, Yasmina Elaribi, Mónica Martinez‐Gallo, Roger Colobran, Angel Sanchez‐Montañez, Irene Valenzuela, Yoshiko Murakami, Alfons Macaya   +11 more
wiley   +1 more source

Seml: A Semantic LSTM Model for Software Defect Prediction

IEEE Access, 2019
Software defect prediction can assist developers in finding potential bugs and reducing maintenance cost. Traditional approaches usually utilize software metrics (Lines of Code, Cyclomatic Complexity, etc.) as features to build classifiers and identify ...
Hongliang Liang, Yue Yu, Lin Jiang, Zhuosi Xie   +3 more
doaj   +1 more source

Neg/pos-Normalized Accuracy Measures for Software Defect Prediction

IEEE Access, 2022
In evaluating the performance of software defect prediction models, accuracy measures such as precision and recall are commonly used. However, most of these measures are affected by neg/pos ratio of the data set being predicted, where neg is the number ...
Maohua Gan, Zeynep Yucel, Akito Monden
doaj   +1 more source