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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2409.18821 |
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| _version_ | 1866916412765765632 |
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| author | Somwase, Sunanda Das, Parismita Sudarshan, S. |
| author_facet | Somwase, Sunanda Das, Parismita Sudarshan, S. |
| contents | Generation of sample data for testing SQL queries has been an important task for many years, with applications such as testing of SQL queries used for data analytics and in application software, as well as student SQL queries. More recently, with the increasing use of text-to-SQL systems, test data is key for the validation of generated queries. Earlier work for test data generation handled basic single block SQL queries, as well as simple nested SQL queries, but could not handle more complex queries. In this paper, we present a novel data generation approach that is designed to handle complex queries, and show its effectiveness on queries for which the earlier XData approach is not as effective. We also show that it can outperform the state-of-the-art VeriEQL system in showing non-equivalence of queries. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_18821 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Data Generation for Testing Complex Queries Somwase, Sunanda Das, Parismita Sudarshan, S. Databases Generation of sample data for testing SQL queries has been an important task for many years, with applications such as testing of SQL queries used for data analytics and in application software, as well as student SQL queries. More recently, with the increasing use of text-to-SQL systems, test data is key for the validation of generated queries. Earlier work for test data generation handled basic single block SQL queries, as well as simple nested SQL queries, but could not handle more complex queries. In this paper, we present a novel data generation approach that is designed to handle complex queries, and show its effectiveness on queries for which the earlier XData approach is not as effective. We also show that it can outperform the state-of-the-art VeriEQL system in showing non-equivalence of queries. |
| title | Data Generation for Testing Complex Queries |
| topic | Databases |
| url | https://arxiv.org/abs/2409.18821 |