Results 91 to 100 of about 111,109 (312)
An Adversarial Discriminative Convolutional Neural Network for Cross-Project Defect Prediction
IEEE Access, 2020 Cross-project defect prediction (CPDP) is a promising approach to help to allocate testing efforts efficiently and guarantee software reliability in the early software lifecycle.
Lei Sheng, Lu Lu, Junhao Lin
doaj +1 more source
, 2018 Deep learning methods are useful for high-dimensional data and are becoming widely used in many areas of software engineering. Deep learners utilizes extensive computational power and can take a long time to train-- making it difficult to widely validate
Arthur David +7 more
core +1 more source
Advanced Engineering Materials, EarlyView.This study demonstrates how optimizing laser power, scanning speed, and hatching distance in laser powder bed fusion can boost the productivity of Inconel 718 manufacturing by up to 29% while maintaining mechanical integrity. The work delivers a validated process window and cost–time analysis, offering industry‐ready guidelines for efficient additive ...
Amir Behjat +7 more
wiley +1 more source
, 2021 Software defect prediction heavily relies on the metrics collected from software projects. Earlier studies often used machine learning techniques to build, validate, and improve bug prediction models using either a set of metrics collected within a project or across different projects. However, techniques applied and conclusions derived by those models
Jahanshahi, Hadi +2 more
openaire +2 more sources
Advanced Engineering Materials, EarlyView.New features on yttria‐stabilized zirconia after exposure at 1500°C: Newly discovered pyramidal structures on an old material. After exposure at 1550°C on the cross section of YSZ new features, namely pyramidal structures are discovered. These structures grow with time, increase in numbers, appear as singularities, are often arranged in strings, and ...
Doris Sebold +2 more
wiley +1 more source
ALTRA: Cross-Project Software Defect Prediction via Active Learning and Tradaboost
IEEE Access, 2020 Cross-project defect prediction (CPDP) methods can be used when the target project is a new project or lacks enough labeled program modules. In these new target projects, we can easily extract and then measure these modules with software measurement ...
Zhidan Yuan +3 more
doaj +1 more source
Towards Defect Phase Diagrams: From Research Data Management to Automated Workflows
Advanced Engineering Materials, EarlyView.A research data management infrastructure is presented for the systematic integration of heterogeneous experimental and simulation data required for defect phase diagrams. The approach combines openBIS with a companion application for large‐object storage, automated metadata extraction, provenance tracking and federated data access, thereby supporting ...
Khalil Rejiba +5 more
wiley +1 more source
A Knowledge‐Based Approach for Understanding and Managing Additive Manufacturing Data
Advanced Engineering Materials, EarlyView.Additive manufacturing processes generate a large amount of data. Effectively managing, understanding, and retrieving information from this data remains a major challenge. Therefore, we propose an ontology‐based approach to integrate heterogeneous data, enable semantic queries, and support decision‐making.
Mina Abd Nikooie Pour +5 more
wiley +1 more source
Negative Transfer in Cross Project Defect Prediction: Effect of Domain Divergence
, 2022 osayande P omondiagbe +2 more
openalex +2 more sources
Integrated Approach to Software Defect Prediction
IEEE Access, 2017 Software defect prediction provides actionable outputs to software teams while contributing to industrial success. Empirical studies have been conducted on software defect prediction for both cross-project and within-project defect prediction.
Ebubeogu Amarachukwu Felix, Sai Peck Lee
doaj +1 more source