Overview
I am a a Gameplay Engineer at Legacy Labs and a Ph.D. candidate at the University of Notre Dame advised by Collin McMillan. My research focuses on the application of virtual assistant technology to software engineering tasks, including source code search and source code summarization. In my spare time, I enjoy designing board games and web applications.
Education
Ph.D. (Expected 2024)
M.S. (2021)
University of Notre Dame
Computer Science and Engineering
B.A. (2017)
Colorado College
Chemistry and Computer Science
Service
- Program Committee Member for IEEE/ACM Mining Software Repositories (MSR) Conference, 2022
- Vice President of the University of Notre Dame Graduate Student Government, 2022
- Social Committee Chair of the University of Notre Dame Graduate Student Government, 2020-2022
Publications
2023
Function Call Graph Context Encoding for Neural Source Code Summarization
Aakash Bansal, Zachary Eberhart, Zachary Karas, Yu Huang, Collin McMillan, "Function Call Graph Context Encoding for Neural Source Code Summarization." In the proceedings of IEEE Transactions on Software Engineering (TSE), 2023.
2022
Semantic Similarity Metrics for Evaluating Source Code Summarization
Sakib Haque, Zachary Eberhart, Collin McMillan, "Semantic Similarity Metrics for Evaluating Source Code Summarization." In the proceedings of 30th IEEE/ACM International Conference on Program Comprehension (ICPC'22), 2022.
Generating Clarifying Questions for Query Refinement in Source Code Search
Zachary Eberhart, Collin McMillan, "Generating Clarifying Questions for Query Refinement in Source Code Search." In the proceedings of 29th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER'22), 2022.
2021
Dialogue Management for Interactive API Search
Zachary Eberhart, Collin McMillan, "Dialogue Management for Interactive API Search." In the proceedings of 37th International Conference on Software Maintenance and Evolution (ICSME'21), 2021.
A Neural Question Answering System for Basic Questions about Subroutines
Aakash Bansal, Zachary Eberhart, Lingfei Wu, Collin McMillan, "A Neural Question Answering System for Basic Questions about Subroutines." In the proceedings of 28th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER'21), 2021.
A Wizard of Oz Study Simulating API Usage Dialogues with a Virtual Assistant
Zachary Eberhart, Aakash Bansal, Collin McMillan, "A Wizard of Oz Study Simulating API Usage Dialogues with a Virtual Assistant." In the proceedings of IEEE Transactions on Software Engineering (TSE), 2021.
2020
Dialogue Act Classification for Virtual Agents for Software Engineers during Debugging
Andrew Wood, Zachary Eberhart, Collin McMillan, "Dialogue Act Classification for Virtual Agents for Software Engineers during Debugging." In the proceedings of IEEE/ACM 8th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE'20), 2020.
A Human Study of Comprehension and Code Summarization
Sean Stapleton, Yashmeet Gambhir, Alexander LeClair, Zachary Eberhart, Westley Weimer, Kevin Leach, Yu Huang, "A Human Study of Comprehension and Code Summarization." In the proceedings of 28th IEEE/ACM International Conference on Program Comprehension (ICPC'20), 2020.
Automatically Extracting Subroutine Summary Descriptions from Unstructured Comments
Zachary Eberhart, Alexander LeClair, Collin McMillan, "Automatically Extracting Subroutine Summary Descriptions from Unstructured Comments." In the proceedings of 27th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER'20), 2020.
The Apiza Corpus: API Usage Dialogues with a Simulated Virtual Assistant
Zachary Eberhart, Aakash Bansal, Collin McMillan, "The Apiza Corpus: API Usage Dialogues with a Simulated Virtual Assistant." Preprint, 2020.
2018
Multi-type itemset embedding for learning behavior success
Daheng Wang, Meng Jiang, Qingkai Zeng, Zachary Eberhart, Nitesh Chawla, "Multi-type itemset embedding for learning behavior success." In the proceedings of Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (SIGKDD'18), 2018.
Adapting neural text classification for improved software categorization
Alexander LeClair, Zachary Eberhart, Collin McMillan, "Adapting neural text classification for improved software categorization." In the proceedings of 2018 IEEE International Conference on Software Maintenance and Evolution (ICSME'18), 2018.