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I-Rex: An Interactive Relational Query Debugger for SQL

Published: 03 March 2022 Publication History

Abstract

Despite the enduring popularity of SQL (Structured Query Language), it is challenging to learn and debug, even for people with considerable programming experience. There is also a lack of SQL tools with advanced debugger features like breakpoints, stepped execution, and variable watching. We present I-Rex, an interactive SQL debugger that enables users to trace the evaluation of a query by its constituent blocks, visualizing how each block computes results from its inputs, and exploring the dependencies among these blocks. I-Rex can be integrated into an autograder, which typically works by comparing the results of submitted queries against reference queries over test database instances. Instead of showing full test instances, which often overwhelm students, I-Rex automatically generates small, illustrative instances for debugging. In this demo, we show how I-Rex helps a student trace complex SQL query execution, learn the semantics of various query constructs, and understand why a query produces (or does not produce) certain results. We also show how a teacher can customize I-Rex for a set of SQL exercises over a database. Overall, we demonstrate how I-Rex supports SQL learning and debugging, thereby increasing students' self-reliance and reducing the burden on the teaching staff.

Cited By

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  • (2024)Technology-Enabled Database Education: Challenges andOpportunitiesACM SIGMOD Record10.1145/3685980.368599253:2(52-53)Online publication date: 31-Jul-2024
  • (2023)Characterizing and Verifying Queries Via CINSGENCompanion of the 2023 International Conference on Management of Data10.1145/3555041.3589721(143-146)Online publication date: 4-Jun-2023

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cover image ACM Conferences
SIGCSE 2022: Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V. 2
March 2022
254 pages
ISBN:9781450390712
DOI:10.1145/3478432
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 March 2022

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Author Tags

  1. database
  2. debugger
  3. relational query
  4. sql

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  • Demonstration

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  • National Science Foundation

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SIGCSE 2022
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Overall Acceptance Rate 1,595 of 4,542 submissions, 35%

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SIGCSE TS 2025
The 56th ACM Technical Symposium on Computer Science Education
February 26 - March 1, 2025
Pittsburgh , PA , USA

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Cited By

View all
  • (2024)Technology-Enabled Database Education: Challenges andOpportunitiesACM SIGMOD Record10.1145/3685980.368599253:2(52-53)Online publication date: 31-Jul-2024
  • (2023)Characterizing and Verifying Queries Via CINSGENCompanion of the 2023 International Conference on Management of Data10.1145/3555041.3589721(143-146)Online publication date: 4-Jun-2023

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