Publications

Journal articles

• Tushar Sharma, Maria Kechagia, Stefanos Georgiou, Rohit Tiwari, Indira Vats, Hadi Moazen, and Federica Sarro. "A Survey on Machine Learning Techniques Applied to Source Code". Accepted in Journal of Systems and Software, Dec 2023. Preprint
• Tushar Sharma, Stefanos Georgiou, Maria Kechagia, Taher A. Ghaleb, and Federica Sarro. "Investigating Developers' Perception on Software Testability and its Effects". Accepted in Empirical Software Engineering Journal, Jul 2023. Preprint
• Chaima Abid, Dhia Elhaq Rzig, Thiago Ferreira, Marouane Kessentini, Tushar Sharma. "X-SBR: On the Use of the History of Refactorings for Explainable Search-Based Refactoring and Intelligent Change Operators", Aug 2021, Transactions on Software Engineering (TSE), doi: 10.1109/TSE.2021.3105037.
• Tushar Sharma, Vasiliki Efstathiou, Panos Louridas, Diomidis Spinellis, "Code Smell Detection by Deep Learning and Transfer Learning", Mar 2021, Volume 176, 2021, 110936, ISSN 0164-1212, doi: 10.1016/j.jss.2021.110936. Preprint

Conference articles

• Tushar Sharma. Multi-faceted Code Smell Detection at Scale using DesigniteJava 2.0. MSR (Data/Tools track) 2024. Preprint
• Saurabh Singh Rajput, Maria Kechagia, Federica Sarro, and Tushar Sharma. Greenlight: Highlighting TensorFlow APIs Energy Footprint. MSR (Data/Tools track) 2024. Preprint
• Mootez Saad and Tushar Sharma. Naturalness of Attention: Revisiting Attention in Code Language Models, Accepted in ICSE (NIER) 2024. Preprint
• Himesh Nandani, Mootez Saad and Tushar Sharma. Calibrating Deep Learning-based Code Smell Detection using Human Feedback, Accepted in IEEE SCAM 2023. Preprint
• Harsh Mukeshkumar Shah, Qurram Zaheer Syed, Bharatwaaj Shankaranarayanan, Indranil Palit, Arshdeep Singh, Kavya Raval, Kishan Savaliya and Tushar Sharma. Mining and Fusing Productivity Metrics with Code Quality Information at Scale, Accepted in IEEE ICSME (Tools track) 2023. Preprint
• Indranil Palit, Gautam Shetty, Hera Arif and Tushar Sharma. Automatic Refactoring Candidate Identification Leveraging Effective Code Representation, Accepted in IEEE ICSME (NIER track) 2023. Preprint
• Himesh Nandani, Mootez Saad, Tushar Sharma. DACOS-A Manually Annotated Dataset of Code Smells. Mining Software Repositories (MSR 2023) - Dataset and tools track. Preprint
• Stefanos Georgiou, Maria Kechagia, Tushar Sharma, Federica Sarro, Ying Zou. Green AI: Do Deep Learning Frameworks Have Different Costs? in 44th International Conference on Software Engineering (ICSE 2022) - Technical track. Preprint
• Akond Rahman, Tushar Sharma. Lessons from Research to Practice on Writing Better Quality Puppet Scripts. in 29th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER), 2022. Pre-print
• Akash Rajesh Agrawal, Sung Jun Won, Mayuri Deshpande, Tushar Sharma, Christopher Carson McComb, "A Multi-Agent Reinforcement Learning Framework for Intelligent Manufacturing with Autonomous Mobile Robots", Apr 21, ICED21 23rd International Conference on Engineering Design.
• Alexandra-Maria Chaniotaki, Tushar Sharma "Architecture Smells and Pareto Principle: A Preliminary Empirical Exploration", MSR 2021 (Research track). Preprint
• Tushar Sharma, Marouane Kessentini. "QScored: A Large Dataset of Code Smells and Quality Metrics", MSR 2021 (Data showcase track). Preprint

Tutorials and technical briefings

• Tushar Sharma. "LLMs for code: the potential, prospects, and problems", International Conference on Software Architecture (ICSA) 2024.

Workshop papers

• Saurabh Singh Rajput and Tushar Sharma. "Pursuit of Energy-efficient AI: Benchmarking Emerging Neural Network Quantization Methods", 8th International Workshop on Green and Sustainable Software (GREENS 2024).

Technical reports

• Tushar Sharma, Maria Kechagia, Stefanos Georgiou, Rohit Tiwari, Indira Vats, Hadi Moazen, Federica Sarro. "A Survey on Machine Learning Techniques for Source Code Analysis", Oct 2021. Available on Arxiv.