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Novice Perceptions on Effective Elements of PostgreSQL Error Messages

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Title: Novice Perceptions on Effective Elements of PostgreSQL Error Messages
Language: English
Authors: Toni Taipalus (ORCID 0000-0003-4060-3431), Hilkka Grahn (ORCID 0000-0001-7567-7807), Saima Ritonummi (ORCID 0000-0001-6708-7639), Valtteri Siitonen (ORCID 0000-0001-7610-4584), Tero Vartiainen (ORCID 0000-0003-3843-8561), Denis Zhidkikh (ORCID 0000-0003-1335-8346)
Source: ACM Transactions on Computing Education. 2025 25(2).
Availability: Association for Computing Machinery. 1601 Broadway 10th Floor, New York, NY 10119. Tel: 800-342-6626; Tel: 212-626-0500; Fax: 212-944-1318; e-mail: acmhelp@acm.org; Web site: http://toce.acm.org/
Peer Reviewed: Y
Page Count: 19
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Computer Science Education, Novices, Information Systems, Programming Languages, Feedback (Response), Syntax, Error Patterns, Natural Language Processing, Computer Mediated Communication, Troubleshooting, Undergraduate Students, Foreign Countries
Geographic Terms: Finland
DOI: 10.1145/3732790
ISSN: 1946-6226
Abstract: SQL compiler error messages are the primary way users receive feedback when they encounter syntax errors or other issues in their SQL queries. Effective error messages can enhance the user experience by providing clear, informative, and actionable feedback. Despite the age of SQL compilers, it still remains largely unclear what contributes to an effective SQL error message. With 2,052 answers yielded by 165 participants for qualitative analysis, this study is an attempt to understand what novices perceive as effective elements in SQL error messages. The results uniformly indicate that communicating the precise error position, articulating what is wrong in the query with clear natural language, and showing hints on how to fix the error are perceived as the most effective elements for error recovery. These insights have potential to be utilized in providing more effective error messages in SQL compilers and SQL learning environments, and for guiding generative AI for enhanced error messages in order to minimize frustration caused by cryptic error messages, improving learning and adoption, and reducing debugging time.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1476240
Database: ERIC
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  Data: Novice Perceptions on Effective Elements of PostgreSQL Error Messages
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  Data: <searchLink fieldCode="AR" term="%22Toni+Taipalus%22">Toni Taipalus</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-4060-3431">0000-0003-4060-3431</externalLink>)<br /><searchLink fieldCode="AR" term="%22Hilkka+Grahn%22">Hilkka Grahn</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-7567-7807">0000-0001-7567-7807</externalLink>)<br /><searchLink fieldCode="AR" term="%22Saima+Ritonummi%22">Saima Ritonummi</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-6708-7639">0000-0001-6708-7639</externalLink>)<br /><searchLink fieldCode="AR" term="%22Valtteri+Siitonen%22">Valtteri Siitonen</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-7610-4584">0000-0001-7610-4584</externalLink>)<br /><searchLink fieldCode="AR" term="%22Tero+Vartiainen%22">Tero Vartiainen</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-3843-8561">0000-0003-3843-8561</externalLink>)<br /><searchLink fieldCode="AR" term="%22Denis+Zhidkikh%22">Denis Zhidkikh</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-1335-8346">0000-0003-1335-8346</externalLink>)
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  Data: SQL compiler error messages are the primary way users receive feedback when they encounter syntax errors or other issues in their SQL queries. Effective error messages can enhance the user experience by providing clear, informative, and actionable feedback. Despite the age of SQL compilers, it still remains largely unclear what contributes to an effective SQL error message. With 2,052 answers yielded by 165 participants for qualitative analysis, this study is an attempt to understand what novices perceive as effective elements in SQL error messages. The results uniformly indicate that communicating the precise error position, articulating what is wrong in the query with clear natural language, and showing hints on how to fix the error are perceived as the most effective elements for error recovery. These insights have potential to be utilized in providing more effective error messages in SQL compilers and SQL learning environments, and for guiding generative AI for enhanced error messages in order to minimize frustration caused by cryptic error messages, improving learning and adoption, and reducing debugging time.
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