Zaineb Sakhrawi

Orcid: 0000-0003-1052-3502

According to our database1, Zaineb Sakhrawi authored at least 13 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of six.
  • Erdős number3 of five.

Timeline

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PhD thesis 
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Bibliography

2024
Test case selection and prioritization approach for automated regression testing using ontology and COSMIC measurement.
Autom. Softw. Eng., November, 2024

Automotive User Interface Based on LSTM-Grid Search Deep Learning Model for IoT Security Change Request Classification.
Proceedings of the Advanced Information Networking and Applications, 2024

2023
On the value of parameter tuning in stacking ensemble model for software regression test effort estimation.
J. Supercomput., October, 2023

2022
Towards an Enhancement Effort Estimation Approach using Machine Learning Techniques. (Vers une approche d'estimation de l'effort d'amélioration en utilisant des techniques d'apprentissage automatique).
PhD thesis, 2022

Support vector regression for enhancement effort prediction of Scrum projects from COSMIC functional size.
Innov. Syst. Softw. Eng., 2022

On the use of OLS regression algorithm and Pearson correlation algorithm for improving the SLA establishment process in cloud computing.
Innov. Syst. Softw. Eng., 2022

Software enhancement effort estimation using correlation-based feature selection and stacking ensemble method.
Clust. Comput., 2022

Software Enhancement Effort Estimation using Stacking Ensemble Model within the Scrum Projects: A Proposed Web Interface.
Proceedings of the 17th International Conference on Software Technologies, 2022

2021
Software Enhancement Effort Prediction Using Machine-Learning Techniques: A Systematic Mapping Study.
SN Comput. Sci., 2021

2020
Investigating the Impact of Functional Size Measurement on Predicting Software Enhancement Effort Using Correlation-Based Feature Selection Algorithm and SVR Method.
Proceedings of the Reuse in Emerging Software Engineering Practices, 2020

An Improved Prediction of Software Enhancement Effort using Correlation-Based Feature Selection and M5P ML Algorithm.
Proceedings of the 17th IEEE/ACS International Conference on Computer Systems and Applications, 2020

2019
Requirements Change Requests Classification: An Ontology-Based Approach.
Proceedings of the Intelligent Systems Design and Applications, 2019

An Ontology-Based Approach for Preventing Incompatibility Problems of Quality Requirements During Cloud SLA Establishment.
Proceedings of the Computational Collective Intelligence - 11th International Conference, 2019


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