Results 41 to 50 of about 155,165 (287)

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

Holistic Parameter Optimization for Software Defect Prediction

IEEE Access, 2022
A software defect prediction (SDP) model identifies the defect-prone modules. Setting appropriate parameters in an SDP model is critical because it affects the model performance.
Jaewook Lee, Jiwon Choi, Duksan Ryu, Suntae Kim   +3 more
doaj   +1 more source

Data quality: Some comments on the NASA software defect datasets [PDF]

, 2013
Background-Self-evidently empirical analyses rely upon the quality of their data. Likewise, replications rely upon accurate reporting and using the same rather than similar versions of datasets.
Mair, C, Shepperd, M, Song, Q, Sun, Z
core   +2 more sources

Structural instability impairs function of the UDP‐xylose synthase 1 Ile181Asn variant associated with short‐stature genetic syndrome in humans

FEBS Letters, EarlyView.
The Ile181Asn variant of human UDP‐xylose synthase (hUXS1), associated with a short‐stature genetic syndrome, has previously been reported as inactive. Our findings demonstrate that Ile181Asn‐hUXS1 retains catalytic activity similar to the wild‐type but exhibits reduced stability, a looser oligomeric state, and an increased tendency to precipitate ...
Tuo Li, Pedro A. Sánchez‐Murcia, Bernd Nidetzky   +2 more
wiley   +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

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

Defect prediction with bad smells in code [PDF]

, 2017
Background: Defect prediction in software can be highly beneficial for development projects, when prediction is highly effective and defect-prone areas are predicted correctly.
Dąbrowska, Marta, Hryszko, Jarosław, Konopka, Piotr, Madeyski, Lech   +3 more
core   +1 more source

Revisiting Unsupervised Learning for Defect Prediction

, 2017
Collecting quality data from software projects can be time-consuming and expensive. Hence, some researchers explore "unsupervised" approaches to quality prediction that does not require labelled data.
Fu, Wei, Menzies, Tim
core   +1 more source

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

Software Defect Prediction Via Deep Learning

International Journal of Innovative Technology and Exploring Engineering, 2020
Existing models on defect prediction are trained on historical limited data which has been studied from a variety of pioneering and researchers. Cross-project defect prediction, which is often reuse data from other projects, works well when the data of training models is completely sufficient to meet the project demands.
Rehan Ullah Khan*, Saleh Albahli, Waleed Albattah, Mohammad Nazrul Islam Khan   +3 more
openaire   +1 more source