Affiliation:
1. University of Jyväskylä, Finland
Abstract
Software developers use a significant amount of time reading and interpreting error messages. However, error messages have often been based on either anecdotal evidence or expert opinion, disregarding novices, who arguably are the ones who benefit the most from effective error messages. Furthermore, the usability aspects of Structured Query Language (SQL) error messages have not received much scientific attention. In this mixed-methods study, we coded a total of 128 error messages from eight database management systems (DBMS), and using data from 311 participants, analysed 4,796 queries using regression analysis to find out if and how acknowledged error message qualities explain SQL syntax error fixing success rates. Additionally, we performed a conventional content analysis on 1,505 suggestions on how to improve SQL error messages, and based on the analysis, formulated a framework consisting of nine guidelines for SQL error message design. The results indicate that general error message qualities do not necessarily explain query fixing success in the context of SQL syntax errors and that even some novel NewSQL systems fail to account for basic error message design guidelines. The error message design framework and examples of its practical applications shown in this study are applicable in educational contexts as well as by DBMS vendors in understanding novice perspectives in error message design.
Publisher
Association for Computing Machinery (ACM)
Cited by
3 articles.
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1. Building Blocks Towards More Effective SQL Error Messages;Proceedings of the 2024 on Innovation and Technology in Computer Science Education V. 1;2024-07-03
2. Exploring Self-Explanations in a Flipped Database Course;Proceedings of the 3rd International Workshop on Data Systems Education: Bridging education practice with education research;2024-06-09
3. How Domain Experts Use an Embedded DSL;Proceedings of the ACM on Programming Languages;2023-10-16