Framework for SQL Error Message Design: A Data-Driven Approach

Author:

Taipalus Toni1ORCID,Grahn Hilkka1ORCID

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)

Subject

Software

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3