Oscar Chaparro

Oscar Chaparro

Wilson & Martha Claiborn Stephens Associate Professor, Director of AI Innovation, William & Mary

Research Lab

SEA Lab Logo

Th Software Evolution and Analysis (SEA) Lab investigates the challenges developers face when maintaining and evolving software, and develops AI-assisted techniques and tools to address them: from managing bug reports and understanding code, to navigating licensing, supply chains, and AI-generated artifacts.

Our research employs empirical methods, analyzes diverse software artifacts (bug reports, source code, online discussions, AI-generated code, etc.), and builds on creating, adapting, and integrating techniques from program analysis, software repository mining (MSR), information retrieval (IR), natural language processing (NLP), computer vision (CV), and machine/deep learning (ML/DL). We are also investigating agentic software engineering: engineering AI agents to effectivelly automate complex SE tasks.

Ph.D. Students

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Antu Saha
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Nathan Wintersgill (*)
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Nadeeshan De Silva
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Mehedi Sun

(*) Co-advised with Denys Poshyvanyk

Master Students

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Sam Bennett

Undergraduate and other Students

  • Justen Hilliard (Undergraduate student)
  • Takashi Idobe (Non-degree-seeking graduate student)

Past Ph.D. Students

  • Trevor Stalnaker (2021 – 2026), Dissertation: Towards Effective Supply Chain Management for Software Systems (PDF: TBA), First position after graduation: Assistant Professor, Department of Computer Science, Washington & Lee University, Lexington, VA

  • Yang Song (2020 – 2024), Dissertation: Automated Bug Report Management to Enhance Software Development, First position after graduation: Co-founder at AiMoray

Past Master Students

  • Grant Enderson (2023 – 2024), Research project: AI-Assisted Generation of Software Bills of Materials for Python Projects, First position after graduation: software engineer intern at Radix Health

Past Undergraduate Students

  • Sam Bennett (2024 – 2026), Research projects: Interactive Bug Reporting with LLMs; Automatically Enhancing Android Bug Reports with LLMs; Multimodal Duplicate Bug Report Detection

  • Kobi Feldman (2022 – 2023), Research project: On the Relationship Between Code Verifiability and Understandability

External Mentees

  • Ahmed Adnan (2023 – 2026), University of Dhaka and East West University, Research projects: SPRINT: An Assistant for Issue Report Management, Rethinking Issue Resolution for AI/ML Systems
  • Mushfiqur Rahman (2025 - 2026), Bangladesh University of Business and Technology (BUBT), Research projects: Rethinking Issue Resolution for AI/ML Systems