Results 41 to 50 of about 4,787,648 (245)

On the Impact of Lower Recall and Precision in Defect Prediction for Guiding Search-Based Software Testing

, 2022
We study the impact of imprecision in defect prediction on the bug detection effectiveness of search-based software testing (SBST). This package is created to support the research community to extend, reproduce and replicate our study in the future.
Anjana Perera (11379750), Marcel Boehme (8502450), Aldeida Aleti (3915431), Burak Turhan (9899144)   +3 more
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

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

Leucine‐rich glioma inactivated 1 (LGI1) is a ganglioside‐binding protein

FEBS Letters, EarlyView.
Neuronal hyperexcitability associated with a decrease/absence of the extracellular protein LGI1 has been suggested to be primarily due to the downregulation of Kv1 channel expression. The molecular mechanisms underlying this decrease have not yet been elucidated.
Kévin Debreux, Christian Lévêque, Fodil Azzaz, Marion Sangiardi, Sarosh R Irani, Michael Seagar, Jacques Fantini, Oussama El Far   +7 more
wiley   +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

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

A Paired Learner-Based Approach for Concept Drift Detection and Adaptation in Software Defect Prediction

, 2021
Kumar, Dr Sandeep/0000-0003-0747-6776; Kumar, Sandeep/0000-0002-3250-4866; Mishra, Alok/0000-0003-1275-2050; Kumar, Sandeep/0000-0001-9633-407XThe early and accurate prediction of defects helps in testing software and therefore leads to an overall higher-
Gangwar, Arvind Kumar, Kumar, Sandeep, Mishra, Alok, Mıshra, Alok   +3 more
core   +1 more source

An Empirical Study on the Effectiveness of Feature Selection for Cross-Project Defect Prediction

IEEE Access, 2019
Software defect prediction has attracted much attention of researchers in software engineering. At present, feature selection approaches have been introduced into software defect prediction, which can improve the performance of traditional defect ...
Qiao Yu, Junyan Qian, Shujuan Jiang, Zhenhua Wu, Gongjie Zhang   +4 more
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

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