Tushar

Tushar Sharma is an Assistant Professor at Dalhousie University, Canada. His research focuses on software code quality, refactoring, sustainable AI, and machine learning for software engineering (ML4SE).

He earned his PhD in Software Engineering from the Athens University of Economics and Business, Greece, in 2019, and an MS in Computer Science from the Indian Institute of Technology–Madras, India. Before joining academia, he worked with Siemens in the USA (2019–2021) and India (2008–2015), gaining extensive research-oriented industry experience.

Tushar is the co-author of Refactoring for Software Design Smells: Managing Technical Debt and two Oracle Java certification books. He is also the founder of Designite, a widely used software design quality assessment tool. He is a Senior Member of IEEE.

He can be reached at tushar@dal.ca.

 

Funded PhD positions at SMART lab@Dalhousie University

If you see your research career in software engineering (specifically but not limited to, software quality, refactoring, code synthesis, and applied machine learning for SE), consider expressing your interest for the positions using this form.

 

News

2025

2024

Click to expand/collapse ...
  • Nov 2024: Participated in the Dagstuhl perspective workshop on "Reframing technical debt". A manifesto will be released in the early 2025. Post of X
  • Oct 2024: Media coverage: "The hidden cost of the AI revolution: carbon emissions"
  • Sept 2024: Media coverage: "This Dal researcher wants to ensure AI doesn’t ruin the environment"
  • Aug 2024: Mitacs Accelerate grant: "Fine-tuning an LLM for patent drafting" ($30K); industry partner: XLSCOUT.
  • Jun 2024: Media coverage: by Daniel Shea about our paper "Code Smell Detection by Deep Direct-Learning and Transfer Learning"-one of the top-cited papers in Journal of systems and software since 2021.
  • Mar 2024: Digital Research Alliance of Canada (DRA) granted computing resources worth more than $51K via Resource Allocation Competition, Co-PI with Dr. Masud Rahman.
  • Mar 2024: Mitacs Accelerate grant: "Exploring the connection between internal and external software quality attributes" ($225K); industry partner: Spokesfan.
  • Mar 2024: Mitacs Accelerate grant: "Subsystem Optimization of Intelligent Automated Distribution Kiosk" ($15K).

2023

Click to expand/collapse ...
  • Sept 2023: Best artifact award for our paper "Calibrating Deep Learning-based Code Smell Detection using Human Feedback" in SCAM 2023.
  • Sept 2023: Lab2Market grant for CoderGate.
  • May 2023: Canada First Research Excellence Fund (CFREF) accepted to fund "Transforming Climate Action: Addressing the Missing Ocean" for $154 million for the next seven years. Glad to be one of the 170 researchers' team from Dalhousie to participate in this program.
  • Apr 2023: Discovery grant proposal - "DevQOps: A Continuous Software Quality Assurance Framework", Accepted to be funded for five years by NSERC.
  • Jan 2023: Lab2Market grant for QConnect.

2021

Click to expand/collapse ...
  • Sept 2021: He joined the Faculty of Computer Science at Dalhousie University, Canada as an assitant professor.
  • Mar-Aug 2021: He served as the PI of DARPA AMP MINDSIGHT team (Siemens, JHU/APL, BAE, UC Irvine).

2019

Click to expand/collapse ...
  • Oct 2019: He joined Siemens Research (formally, Siemens Technology), Charlotte, USA.
  • May 2019: He defended his PhD thesis titled "Extending Maintainability Analysis Beyond Code Smells". Thesis.

Recent publications

2025

  • "Grounding Generative AI in Software Engineering: Are We There Yet?". Accepted in SANER 2026 (Early Research Achievements track). Dec 2025. Preprint
  • "RefineID: A Developer-Centric IDE Assistant for Better Identifiers". Accepted in SANER 2026 (Tools track). Dec 2025. Preprint
  • "FlipFlop: A Static Analysis-based Energy Optimization Framework for GPU Kernels". Accepted in ICSE 2026 (Research track). Dec 2025. Preprint
  • "CONCORD: A DSL for Generating Simplified and Scalable Graph-Based Code Representations". Accepted in SANER (Research track) 2026. Dec 2025. Preprint
  • "Mind the Merge: Evaluating the Effects of Token Merging on Pre-trained Models for Code". Accepted in SANER (Research track) 2026.
  • "Tu(r)ning AI Green: Exploring Energy Efficiency Cascading with Orthogonal Optimizations". Accepted in IEEE Software (Special issue on Green Clean Software Sustainability), 2026. Dec 2025. Preprint
  • "Why Attention Fails: A Taxonomy of Faults in Attention-Based Neural Networks". Accepted in ICSE (Research track) 2026. Oct 2025.
  • Community-Centered Spatial Intelligence for Climate Adaptation at Nova Scotia's Eastern Shore. Accepted in SpatialConnect 2025, Sept 2025.
  • "Mapping Code Smells and Refactorings Accurately: Insights from an Empirical Study". Accepted in ESEM (Research track) 2025. June 2025. Preprint
  • "Reinforcement~Learning vs Supervised~Learning: A tug of war to generate refactored code accurately". Accepted in EASE (Research track) 2025. March 2025. Preprint
  • "An adaptive language-agnostic pruning method for greener language models for code". Accepted in FSE (Research track) 2025. Jan 2025. Preprint
  • "MaRV: A Manually Validated Refactoring Dataset". Accepted in FORGE 2025 (Benchmarking track). Jan 2025.
  • "DPy: Code Smells Detection Tool for Python". Accepted in MSR (tools track) 2025. Jan 2025. Preprint
  • "It Works (only) on My Machine: A Study on Reproducibility Smells in Ansible Scripts". Accepted in MSR (research track) 2025. Jan 2025. Preprint

2024

Click to expand/collapse ...

2023

Click to expand/collapse ...
  • "A Survey on Machine Learning Techniques Applied to Source Code", Accepted in Journal of Systems and Software, Dec 2023. Preprint
  • "Naturalness of Attention: Revisiting Attention in Code Language Models", Accepted in ICSE (NIER), Nov 2023. Preprint
  • "Calibrating Deep Learning-based Code Smell Detection using Human Feedback", Accepted in IEEE SCAM, Aug 2023. Preprint
  • "Mining and Fusing Productivity Metrics with Code Quality Information at Scale", Accepted in IEEE ICSME (Tools track), Aug 2023. Preprint
  • "Automatic Refactoring Candidate Identification Leveraging Effective Code Representation", Accepted in IEEE ICSME (NIER track), Aug 2023. Preprint
  • "Investigating Developers' Perception on Software Testability and its Effects", Accepted in Empirical Software Engineering Journal (EMSE), Jul 2023. Preprint
  • "DACOS-A Manually Annotated Dataset of Code Smells", MSR 2023 (dataset and tools track). Preprint

2022

Click to expand/collapse ...
  • "Green AI: Do Deep Learning Frameworks Have Different Costs?", ICSE 2022 (Research track). Preprint
  • "Lessons from Research to Practice on Writing Better Quality Puppet Scripts", SANER 2022. Preprint

2021

Click to expand/collapse ...

2020

Click to expand/collapse ...

2019

Click to expand/collapse ...

You may find the complete list of publications here.

Teaching

Service

Talks

  • "Looking Deep Learning Frameworks Through Sustainability Lens" at 2022 CTRI Research Day on Aug 11, 2022.
  • Smelling Source Code Using Deep Learning at FOSDEM 2019.
  • A workshop on technical debt at Citrix, Banglore on Nov 12, 2018.
  • "Tracking Smells for Effective Maintainability Improvements" on Oct 6, 2018 at Software Architects meetup, Bangalore.
  • A session on TDD at Microsoft development center, Hyderabad on Aug 27, 2018.
  • "How deep is the mud: Identifying technical debt using Eclipse JDT" at Eclipse Day India on Sept 22, 2018
  • Talk at Technical Agility Conference, Bangalore - "Does Your Architecture Smell?"
  • "Understanding and Improving Software Quality" at Singular Logic, Athens on May 11, 2018
  • "What I Learned about Code Smells from Studying ~700 Studies" Programming Language seminar at University of Athens on Dec 29, 2017
  • "Understanding smells for higher software quality" at Singular Logic, Athens on Sept 5, 2017.
  • "Does your configuration code smell?" at FOSDEM, Brussels on Feb 4, 2017.