Results 51 to 60 of about 131,864 (294)
Software Fault Prediction at Design Phase
Journal of Electrical Engineering and Technology, 2014 Prediction of fault-prone modules continues to attract researcher’s interest due to its significant impact on software development cost. The most important goal of such techniques is to correctly identify the modules where faults are most likely to present in early phases of software development lifecycle.
Pradeep Singh, Shrish Verma, O.P. Vyas
openaire +2 more sources
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 +9 more
wiley +1 more source
Are Smell-Based Metrics Actually Useful in Effort-Aware Structural Change-Proneness Prediction? An Empirical Study [PDF]
, 2019 Bad code smells (also named as code smells) are symptoms of poor design choices in implementation. Existing studies empirically confirmed that the presence of code smells increases the likelihood of subsequent changes (i.e., change-proness).
Jia, Ru +4 more
core +1 more source
FEBS Letters, EarlyView.This study reveals a unique active site enriched in methionine residues and demonstrates that these residues play a critical role by stabilizing carbocation intermediates through novel sulfur–cation interactions. Structure‐guided mutagenesis further revealed variants with significantly altered product profiles, enhancing pseudopterosin formation. These
Marion Ringel +13 more
wiley +1 more source
Applied Sciences, 2021 Many NHPP software reliability growth models (SRGMs) have been proposed to assess software reliability during the past 40 years, but most of them have focused on modeling the fault detection process (FDP) in two ways: one is to ignore the fault ...
Qiuying Li, Hoang Pham
doaj +1 more source
Molecular Oncology, EarlyView.ERRFI1, a neural crest (NC)‐associated gene, was upregulated in melanoma and negatively correlated with the expression of melanocytic differentiation markers and the susceptibility of melanoma cells toward BRAF inhibitors (BRAFi). Knocking down ERRFI1 significantly increased the sensitivity of melanoma cells to BRAFi.
Nina Wang +8 more
wiley +1 more source
Improved prediction of software defect: A particle swarm optimization based ELM approach
e-Prime: Advances in Electrical Engineering, Electronics and EnergyEnsuring software reliability before deployment is essential, as human errors during development are a major source of defects. Identifying and resolving these issues at an early stage can greatly minimize their impact.
Debasish Pradhan, Debendra Muduli
doaj +1 more source
Cell surface interactome analysis identifies TSPAN4 as a negative regulator of PD‐L1 in melanoma
Molecular Oncology, EarlyView.Using cell surface proximity biotinylation, we identified tetraspanin TSPAN4 within the PD‐L1 interactome of melanoma cells. TSPAN4 negatively regulates PD‐L1 expression and lateral mobility by limiting its interaction with CMTM6 and promoting PD‐L1 degradation.
Guus A. Franken +7 more
wiley +1 more source
Evaluating the Assessment of Software Fault-Freeness [PDF]
, 2014 We propose to validate experimentally a theory of software certification that proceeds from assessment of confidence in fault-freeness (due to standards) to conservative prediction of failure-free ...
Littlewood, B., Rushby, J., Strigini, L.
core +1 more source
Amortising the Cost of Mutation Based Fault Localisation using Statistical Inference
, 2019 Mutation analysis can effectively capture the dependency between source code and test results. This has been exploited by Mutation Based Fault Localisation (MBFL) techniques.
An, Gabin +3 more
core +1 more source