Graph-based QSS: A Graph-based Approach to Quantifying Semantic Similarity for Automated Linear SQL Grading

Köberlein L, Probst D, Lenz R (2025)

Publication Type: Conference contribution

Publication year: 2025

Publisher: Gesellschaft für Informatik

Series: P361 - BTW2025 - Datenbanksysteme für Business, Technologie und Web

City/Town: Bonn

Event location: Bamberg DE

DOI: 10.18420/BTW2025-13

Abstract

Determining the Quantified Semantic Similarity (QSS) between database queries is a critical challenge with broad applications, from query log analysis to automated SQL skill assessment. Traditional methods often rely solely on syntactic comparisons or are limited to checking for semantic equivalence. This paper introduces Graph-based QSS, a novel graph-based approach to measure the semantic dissimilarity between SQL queries. Queries are represented as nodes in an implicit graph, while the transitions between nodes are called edits, which are weighted by semantic dissimilarity. We employ shortest path algorithms to identify the lowest-cost edit sequence between two given queries, thereby defining a quantifiable measure of semantic distance. An empirical study of our prototype suggests that our method provides more accurate and comprehensible grading compared to existing techniques. Moreover, the results indicate that our approach comes close to the quality of manual grading, making it a robust tool for diverse database query comparison tasks.

Authors with CRIS profile

Leo Köberlein Chair of Visual Computing (LGDV) Dominik Probst Chair for Computer Science 6 (Data Management) Richard Lenz Professur für evolutionäres Datenmanagement

How to cite

APA:

Köberlein, L., Probst, D., & Lenz, R. (2025). Graph-based QSS: A Graph-based Approach to Quantifying Semantic Similarity for Automated Linear SQL Grading. In Proceedings of the Datenbanksysteme für Business, Technologie und Web (BTW 2025). Bamberg, DE: Bonn: Gesellschaft für Informatik.

MLA:

Köberlein, Leo, Dominik Probst, and Richard Lenz. "Graph-based QSS: A Graph-based Approach to Quantifying Semantic Similarity for Automated Linear SQL Grading." Proceedings of the Datenbanksysteme für Business, Technologie und Web (BTW 2025), Bamberg Bonn: Gesellschaft für Informatik, 2025.

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