Using Bio-Inspired Features Selection Algorithms in Software Effort Estimation: A Systematic Literature Review. - Asad Ali 006; Carmine Gravino (SEAA, 2019)

A systematic literature review of software effort prediction using machine learning methods. - Asad Ali 006; Carmine Gravino (J. Softw. Evol. Process., 2019)

Software Fault Prediction using Bio-Inspired Algorithms to Select the Features to be employed: An Empirical Study. - Asad Ali 006; Carmine Gravino (ISD, 2021)

Improving software effort estimation using bio-inspired algorithms to select relevant features: An empirical study. - Asad Ali 006; Carmine Gravino (Sci. Comput. Program., 2021)

An empirical comparison of validation methods for software prediction models. - Asad Ali 006; Carmine Gravino (J. Softw. Evol. Process., 2021)

The Impact of Parameters Optimization in Software Prediction Models. - Asad Ali 006; Carmine Gravino (SEAA, 2022)

Evaluating the impact of feature selection consistency in software prediction. - Asad Ali 006; Carmine Gravino (Sci. Comput. Program., 2022)

Using Permutation-Based Feature Importance for Improved Machine Learning Model Performance at Reduced Costs. - Adam Khan; Asad Ali 006; Jahangir Khan; Fasee Ullah; Muhammad Faheem 003 (IEEE Access, 2025)

Exploring Consistent Feature Selection for Software Fault Prediction: An XAI-Based Model-Agnostic Approach. - Adam Khan; Asad Ali 006; Jahangir Khan; Fasee Ullah; Muhammad Faheem 003 (IEEE Access, 2025)