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Hamoud Aljamaan
Hamoud Aljamaan
Assistant Professor, KFUPM
Verified email at uottawa.ca - Homepage
Title
Cited by
Cited by
Year
Three empirical studies on predicting software maintainability using ensemble methods
MO Elish, H Aljamaan, I Ahmad
Soft Computing 19, 2511-2524, 2015
742015
Bad smell detection using machine learning techniques: a systematic literature review
A Al-Shaaby, H Aljamaan, M Alshayeb
Arabian Journal for Science and Engineering 45 (4), 2341-2369, 2020
642020
Software defect prediction using tree-based ensembles
H Aljamaan, A Alazba
Proceedings of the 16th ACM International Conference on Predictive Models …, 2020
632020
An empirical study of bagging and boosting ensembles for identifying faulty classes in object-oriented software
HI Aljamaan, MO Elish
2009 IEEE symposium on computational intelligence and data mining, 187-194, 2009
542009
Code smell detection using feature selection and stacking ensemble: An empirical investigation
A Alazba, H Aljamaan
Information and Software Technology, 106648, 2021
432021
Impact of hyperparameter tuning on machine learning models in stock price forecasting
KE Hoque, H Aljamaan
IEEE Access 9, 163815-163830, 2021
402021
Umple: A framework for model driven development of object-oriented systems
MA Garzón, H Aljamaan, TC Lethbridge
2015 ieee 22nd international conference on software analysis, evolution, and …, 2015
362015
Enhanced Code Generation from UML Composite State Machines
O Badreddin, TC Lethbridge, A Forward, M Elaasar, H Aljamaan, ...
2nd International Conference on Model-Driven Engineering and Software …, 2014
362014
Umple: Model-driven development for open source and education
TC Lethbridge, A Forward, O Badreddin, D Brestovansky, M Garzon, ...
Science of Computer Programming 208, 102665, 2021
302021
An ensemble of computational intelligence models for software maintenance effort prediction
H Aljamaan, MO Elish, I Ahmad
Advances in Computational Intelligence: 12th International Work-Conference …, 2013
232013
Reverse engineering of object-oriented code into Umple using an incremental and rule-based approach.
MA Garzón, TC Lethbridge, H Aljamaan, O Badreddin
CASCON 14, 91-105, 2014
202014
Software Defect Prediction Using Stacking Generalization of Optimized Tree-Based Ensembles
A Alazba, H Aljamaan
Applied Sciences 12 (9), 4577, 2022
192022
Specifying Trace Directives for UML Attributes and State Machines
H Aljamaan, TC Lethbridge, O Badreddin, G Guest, A Forward
2nd International Conference on Model-Driven Engineering and Software …, 2014
192014
Aware: Aspect-based sentiment analysis dataset of apps reviews for requirements elicitation
N Alturaief, H Aljamaan, M Baslyman
2021 36th IEEE/ACM International Conference on Automated Software …, 2021
132021
Deep learning approaches for bad smell detection: a systematic literature review
A Alazba, H Aljamaan, M Alshayeb
Empirical Software Engineering 28 (3), 77, 2023
122023
MOTL: a textual language for trace specification of state machines and associations
H Aljamaan, TC Lethbridge, MA Garzón
Proceedings of the 25th Annual International Conference on Computer Science …, 2015
122015
Towards tracing at the model level
H Aljamaan, TC Lethbridge
2012 19th Working Conference on Reverse Engineering, 495-498, 2012
112012
Python code smells detection using conventional machine learning models
R Sandouka, H Aljamaan
PeerJ Computer Science 9, e1370, 2023
82023
Voting heterogeneous ensemble for code smell detection
H Aljamaan
2021 20th IEEE international conference on machine learning and applications …, 2021
82021
UmpleRun: a Dynamic Analysis Tool for Textually Modeled State Machines using Umple.
H Aljamaan, T Lethbridge, M Garzón, A Forward
EXE@ MoDELS, 16-20, 2015
82015
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