Results 131 to 140 of about 198,133 (331)

A Study on Predicting Defects in Software

, 2022
For the purpose of creating software defect metrics, data from software repositories such as code complexity and change records is used to build machine learning classifiers that can detect problematic code snippets. For IT SME's, this study piece aims to provide light on the correlations between numerous variables. The data is analysed and interpreted
openaire   +2 more sources

Semantic Methods In Software Defect Prediction Techniques [PDF]

The traditional methods in software defect prediction use software metrics that are collected from the source code. However these methods have an important shortcoming: it is possible that two source code segments, where one is buggy and one is not, have
Işıkoğlu, Şükrücan Taylan
core  

Additive Manufacturing of Continuous Fibre Reinforced Composites: Process, Characterisation, Modelling, and Sustainability

Advanced Engineering Materials, EarlyView.
Additive manufacturing provides precise control over the placement of continuous fibres within polymer matrices, enabling customised mechanical performance in composite components. This article explores processing strategies, mechanical testing, and modelling approaches for additive manufactured continuous fibre‐reinforced composites.
Cherian Thomas, Amir Hosein Sakhaei
wiley   +1 more source

Phase Field Failure Modeling: Brittle‐Ductile Dual‐Phase Microstructures under Compressive Loading

Advanced Engineering Materials, EarlyView.
The approach by Amor and the approach by Miehe and Zhang for asymmetric damage behavior in the phase field method for fracture are compared regarding their fitness for microcrack‐based failure modeling. The comparison is performed for the case of a dual‐phase microstructure with a brittle and a ductile constituent.
Jakob Huber, Jan Torgersen, Ewald Werner
wiley   +1 more source

Naive Bayes Classification for Software Defect Prediction

Transactions on Informatics and Data Science
Software defects are an inevitable aspect of software development, exerting substantial influence on the reliability and performance of software applications.
Edwin Hari Agus Prastyo, Muhammad Ainul Yaqin, Suhartono, M. Faisal, Reza Augusta Jannatul Firdaus   +4 more
doaj   +1 more source

Contributing Features-Based Schemes for Software Defect Prediction [PDF]

, 2019
Automated defect prediction of large and complex software systems is a challenging task. However, by utilising correlated quality metrics, a defect prediction model can be devised to automatically predict the defects in a software system.
Mcclean, Sally, Zhiwei Lin, Abu-tair, Mamun, Lin, Zhiwei, Mamun Abu-Tair, Ian McChesney, Mcchesney, Ian, Noppen, Joost, Aftab Ali, Joost Noppen, Sally McClean, Ali, Aftab   +11 more
core   +1 more source

Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying

Advanced Engineering Materials, EarlyView.
An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara, Vincent Rat, Quentin Dubreuil, Patrice Valorge, Simon Goutier, Alain Denoirjean, Olivier Messe, Céline Ruelle, Jean‐Philippe Poli   +8 more
wiley   +1 more source

DEFECT SEVERITY CODE PREDICTION BASED ON ENSEMBLE LEARNING

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
In machine learning, learning algorithms that learn from other algorithms are called meta-learning. New algorithms called Ensemble algorithms have surfaced as a viable method to improve defect prediction models' accuracy and dependability.
Ghada Mohammad Tahir Aldabbagh, Safwan Omar Hasoon   +1 more
doaj   +1 more source

Toward Knowledge‐Based Workflows: A Semantic Approach to Atomistic Simulations for Mechanical and Thermodynamic Properties

Advanced Engineering Materials, EarlyView.
Knowledge‐based atomistic workflows are presented for mechanical and thermodynamic properties. By coupling modular simulations with ontology‐aligned metadata and provenance, Fe case studies on elastic behavior, defects, thermal properties, and Hall–Petch strengthening reveal how FAIR, queryable, and reusable simulation data can be generated. Mechanical
Abril Azócar Guzmán, Hoang‐Thien Luu, Sarath Menon, Tilmann Hickel, Nina Merkert, Stefan Sandfeld   +5 more
wiley   +1 more source

data unpredictability in software defect-fixing effort prediction

, 2010
National Laboratory for Parallel and Distributed Processing; The University of Hong KongThe prediction of software defect-fixing effort is important for strategic resource allocation and software quality management.
Wang Qing, Yang Ye, He Zhimin, Zhang Wen, Shu Fengdi   +4 more
core