Results 31 to 40 of about 526 (209)

Extracting software static defect models using data mining

Ain Shams Engineering Journal, 2015
Large software projects are subject to quality risks of having defective modules that will cause failures during the software execution. Several software repositories contain source code of large projects that are composed of many modules. These software
Ahmed H. Yousef
doaj   +1 more source

Phosphatidylinositol 4‐kinase as a target of pathogens—friend or foe?

FEBS Letters, EarlyView.
This graphical summary illustrates the roles of phosphatidylinositol 4‐kinases (PI4Ks). PI4Ks regulate key cellular processes and can be hijacked by pathogens, such as viruses, bacteria and parasites, to support their intracellular replication. Their dual role as essential host enzymes and pathogen cofactors makes them promising drug targets.
Ana C. Mendes, Guilherme M. Azevedo, Amanda P. Barcellos, Diana Bahia   +3 more
wiley   +1 more source

FORESIGHT: Software Defects Prediction from Requirements Change Requests Using Machine Learning Methods

Systems
Software defect prediction is becoming key for software quality assurance. Traditional software defect prediction approaches have predominantly focused on analyzing code-level metrics, often overlooking valuable information available during the ...
Hanan Helwa, Adel Taweel
doaj   +1 more source

Transferrin receptor 1‐mediated iron uptake supports thermogenic activation in human cervical‐derived adipocytes

FEBS Letters, EarlyView.
In this study, we found that human cervical‐derived adipocytes maintain intracellular iron level by regulating the expression of iron transport‐related proteins during adrenergic stimulation. Melanotransferrin is predicted to interact with transferrin receptor 1 based on in silico analysis.
Rahaf Alrifai, Mizuki Seo, Gyath Karadsheh, Fachrur Rizal Mahendra, Máté Á Demény, Ferenc Győry, János András Mótyán, László Fésüs, Endre Kristóf, Rini Arianti   +9 more
wiley   +1 more source

Software Defect Prediction by Online Learning Considering Defect Overlooking

2023 IEEE 34th International Symposium on Software Reliability Engineering Workshops (ISSREW), 2023
2 ...
Yamasaki, Yuta, Fedorov, Nikolay, Tsunoda, Masateru, Monden, Akito, Tahir, Amjed, Bennin, Kwabena, Toda, Koji, Nakasai, Keitaro   +7 more
openaire   +3 more sources

Machine Learning Approaches for Software Defect Prediction

Applied Computational Intelligence and Soft Computing
This paper analyses existing research about machine learning approaches in software defect prediction as a key element for improving software reliability and quality.
Hijab Zehra Zaidi, Ubaid Ullah, Muddassira Arshad, Hanan Aljuaid, Muhammad Arslan Rauf, Nadeem Sarwar, Rimsha Sajid   +6 more
doaj   +1 more source

Validating Unsupervised Machine Learning Techniques for Software Defect Prediction With Generic Metamorphic Testing

IEEE Access
In the realm of software defect prediction, unsupervised models often step in when labelled datasets are scarce, despite facing the challenge of validating models without prior knowledge of data.
Pak Yuen Patrick Chan, Jacky Keung
doaj   +1 more source

Software Defect Density Prediction Using Deep Learning

IEEE Access, 2022
Delivering a reliable and high-quality software system to client is a big challenge in software development and evolution process. One of the software measures that confirm the quality of the system is the defect density.
Firas Alghanim, Mohammad Azzeh, Ammar El-Hassan, Hazem Qattous   +3 more
doaj   +1 more source

The planar cell polarity protein Vangl2 interacts with the PDZ‐domains of Scribble but not with a unique PDZ‐like domain in Inturned

FEBS Letters, EarlyView.
Structural and biochemical characterisations show that the planar cell polarity (PCP) protein Inturned harbours a unique PDZ‐like domain that does not bind canonical PDZ‐binding motifs (PBMs) like that of another PCP protein Vangl2. In contrast, the apical‐basal polarity protein Scribble contains four PDZ domains that bind Vangl2, but one PDZ domain ...
Stephan Wilmes, Jan Brysch, Carmen Gelze, Lilli Meier, Daniel Kümmel   +4 more
wiley   +1 more source

A novel kernel to predict software defectiveness

Journal of Systems and Software, 2016
We propose new kernels for defect prediction that are based on the source code similarity.We model the relationship between source code similarity and defectiveness.The precomputed kernels are used with SVM and KNN classifiers.The proposed technique performs better than the SVM with linear kernel.It also achieves comparable performance when compared to
Ahmet Okutan, Olcay Taner Yildiz
openaire   +1 more source