DACOS - A Manually Annotated Dataset of Code Smells. - Himesh Nandani; Mootez Saad; Tushar Sharma 001 (MSR, 2023)

Calibrating Deep Learning-based Code Smell Detection using Human Feedback. - Himesh Nandani; Mootez Saad; Tushar Sharma 001 (SCAM, 2023)

On Inter-dataset Code Duplication and Data Leakage in Large Language Models. - José Antonio Hernández López; Boqi Chen; Mootez Saad; Tushar Sharma 001; Dániel Varró (Zenodo, 2023)

Naturalness of Attention: Revisiting Attention in Code Language Models. - Mootez Saad; Tushar Sharma 001 (NIER@ICSE, 2024)

Enhancing Identifier Naming Through Multi-Mask Fine-Tuning of Language Models of Code. - Sanidhya Vijayvargiya; Mootez Saad; Tushar Sharma 001 (SCAM, 2024)

CONCORD: Towards a DSL for Configurable Graph Code Representation. - Mootez Saad; Tushar Sharma 001 (CoRR, 2024)

ALPINE: An adaptive language-agnostic pruning method for language models for code. - Mootez Saad; José Antonio Hernández López; Boqi Chen; Dániel Varró; Tushar Sharma 001 (CoRR, 2024)

An Adaptive Language-Agnostic Pruning Method for Greener Language Models for Code. - Mootez Saad; José Antonio Hernández López; Boqi Chen; Dániel Varró; Tushar Sharma 001 (Proc. ACM Softw. Eng., 2025)

On Inter-Dataset Code Duplication and Data Leakage in Large Language Models. - José Antonio Hernández López; Boqi Chen; Mootez Saad; Tushar Sharma 001; Dániel Varró (IEEE Trans. Software Eng., 2025)

SENAI: Towards Software Engineering Native Generative Artificial Intelligence. - Mootez Saad; José Antonio Hernández López; Boqi Chen; Neil A. Ernst; Dániel Varró; Tushar Sharma 001 (CoRR, 2025)

Tu(r)ning AI Green: Exploring Energy Efficiency Cascading with Orthogonal Optimizations. - Saurabhsingh Rajput; Mootez Saad; Tushar Sharma 001 (CoRR, 2025)

On the Effect of Token Merging on Pre-trained Models for Code. - Mootez Saad; Hao Li 094; Tushar Sharma 001; Ahmed E. Hassan (CoRR, 2025)