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How Database Theory Helps Teach Relational Queries in Database Education (Invited Talk)

Authors Sudeepa Roy , Amir Gilad , Yihao Hu , Hanze Meng , Zhengjie Miao , Kristin Stephens-Martinez , Jun Yang

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Subject Classification

ACM Subject Classification
  • Theory of computation → Database theory
  • Information systems → Data management systems
  • Information systems → Structured Query Language
Keywords
  • Query Debugging
  • SQL
  • Relational Algebra
  • Relational Calculus
  • Database Education
  • Boolean Provenance

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Abstract

Data analytics skills have become an indispensable part of any education that seeks to prepare its students for the modern workforce. Essential in this skill set is the ability to work with structured relational data. Relational queries are based on logic and may be declarative in nature, posing new challenges to novices and students. Manual teaching resources being limited and enrollment growing rapidly, automated tools that help students debug queries and explain errors are potential game-changers in database education. We present a suite of tools built on the foundations of database theory that has been used by over 1600 students in database classes at Duke University, showcasing a high-impact application of database theory in database education.

Cite As Get BibTex

Sudeepa Roy, Amir Gilad, Yihao Hu, Hanze Meng, Zhengjie Miao, Kristin Stephens-Martinez, and Jun Yang. How Database Theory Helps Teach Relational Queries in Database Education (Invited Talk). In 27th International Conference on Database Theory (ICDT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 290, pp. 2:1-2:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024) https://doi.org/10.4230/LIPIcs.ICDT.2024.2

Author Details

Sudeepa Roy
  • Duke University, Durham, NC, USA
  • RelationalAI, Berkeley, CA, USA (Visiting Scientist)
Amir Gilad
  • Hebrew University of Jerusalem, Israel
Yihao Hu
  • Duke University, Durham, NC, USA
Hanze Meng
  • Duke University, Durham, NC, USA
Zhengjie Miao
  • Simon Fraser University, Burnaby, Canada
Kristin Stephens-Martinez
  • Duke University, Durham NC, USA
Jun Yang
  • Duke University, Durham, NC, USA

Funding

This work was partially supported by NSF awards IIS-2008107 and IIS-1552538.

Acknowledgements

The authors are grateful to graduate and undergraduate students Alexander Bendeck, Stephen Chen, Tiangang Chen, Jeremy Cohen, Kevin Day, James Leong, Qiulin Li, James Lim, Jeffrey Luo, Allen Pan, Aanya Sanghavi, Sharan Sokhi, Aparimeya Taneja, and Zachary Zheng who contributed to building the tracing tool for SQL queries. This work was done when Zhengjie Miao (part of his PhD dissertation research) and Amir Gilad were at Duke University.

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