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Author

Asad Ali

Observed name: Ali, Asad
ORCID: 0000-0001-7465-1090
Observed ORCID: 0000-0001-7465-1090
OpenAlex ID: A5101987074
A systematic literature review of software effort prediction using machine learning methods
2019 · Asad Ali, Carmine Gravino · Journal of Software Evolution and Process · 102
Using Permutation-Based Feature Importance for Improved Machine Learning Model Performance at Reduced Costs
2025 · Adam Khan, Asad Ali, et al. · IEEE Access · 73
Improving software effort estimation using bio-inspired algorithms to select relevant features: An empirical study
2021 · Asad Ali, Carmine Gravino · Science of Computer Programming · 39
An empirical comparison of validation methods for software prediction models
2021 · Asad Ali, Carmine Gravino · Journal of Software Evolution and Process · 25
Clustering APT Groups Through Cyber Threat Intelligence by Weighted Similarity Measurement
2024 · Zheng-Shao Chen, R. Vaitheeshwari, et al. · IEEE Access · 22
Artificial Neural Networks for Sensor Data Classification on Small Embedded Systems
2020 · Venzke, Marcus, Klisch, Daniel, et al. · arXiv (Cornell University) · 17
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Evaluating the impact of feature selection consistency in software prediction
2021 · Asad Ali, Carmine Gravino · Science of Computer Programming · 16
Intelligent Pedestrian Detection using Optical Flow and HOG
2016 · Huma Ramzan, Bahjat Fatima, et al. · International Journal of Advanced Computer Science and Applications · 11
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Adaptive game-based e-leaming using semantic web technologies
2017 · Asad Ali, Melike Sah · International Conference on Open Source Systems and Technologies (ICOSST) · 9
Bio-inspired Algorithms in Software Fault Prediction: A Systematic Literature Review
2020 · Asad Ali, Carmine Gravino · International Conference on Open Source Systems and Technologies (ICOSST) · 8
Using Bio-Inspired Features Selection Algorithms in Software Effort Estimation: A Systematic Literature Review
2019 · Asad Ali, Carmine Gravino · Euromicro Conference on Software Engineering and Advanced Applications (SEAA) · 7
Exploring Consistent Feature Selection for Software Fault Prediction: An XAI-Based Model-Agnostic Approach
2025 · Adam Khan, Asad Ali, et al. · IEEE Access · 6
Explainable Artificial Intelligence in Software Engineering: Current Trends, Gaps, and Future Directions
2026 · Adam Khan, Asad Ali, et al. · IEEE Access · 5
Using Combinations of Bio-inspired Feature Selection Algorithms in Software Efforts Estimation: An Empirical Study
2019 · Asad Ali, Carmine Gravino · International Conference on Open Source Systems and Technologies (ICOSST) · 5
A Systematic Literature Review of Explainable Artificial Intelligence (XAI) in Software Engineering (SE)
2023 · Adam khan, Asad Ali, et al. · Research Square · 4
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Inference New Knowledge Using Sparql Construct Query
2019 · Asad Ali, Owais Qayyum · International Conference on Computing, Mathematics and Engineering Technologies (iCoMET) · 4
An Ontology-Based Approach to Semi-Automate Systematic Literature Reviews
2018 · Asad Ali, Carmine Gravino · International Conference on Open Source Systems and Technologies (ICOSST) · 4
Modified LVQ based clustering analysis for decision making in construction management
2015 · Muhammad Naveed Riaz, Syed Afaq Husain, et al. · International Conference on Open Source Systems and Technologies (ICOSST) · 3
The Impact of Parameters Optimization in Software Prediction Models
2022 · Asad Ali, Carmine Gravino · Euromicro Conference on Software Engineering and Advanced Applications (SEAA) · 2
Explainable Machine Learning for Predicting Dengue Recovery Duration: Insights from Multi-Center Clinical Data
2026 · Adam Khan, Asad Ali, et al. · Healthcare
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Impact of class balancing techniques or events per variable ratio on the conclusion of the software faults prediction models
2025 · Asad Ali, Dost Muhammad, et al. · Innovations in Systems and Software Engineering
Software Fault Prediction using Bio-Inspired Algorithms to Select the Features to be employed: An Empirical Study
2021 · Asad Ali, Carmine Gravino · Journal of the Association for Information Systems
Works count: 22
Citation count: 362
H-index: 9
I10-index: 8
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