# test data

Published articles for test data.

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## New things for regular expressions in PostgreSQL (pg\_tre and pg\_re2)

DevFeed: [New things for regular expressions in PostgreSQL (pg\_tre and pg\_re2)](<https://devfeed.tech/articles/new-things-for-regular-expressions-in-postgresql-pg-tre-and-pg-re2-33694.md>)

Original publisher: [Read original article](<https://www.depesz.com/2026/08/25/new-things-for-regular-expressions-in-postgresql-pg_tre-and-pg_re2/>)

Author: depesz

Published: 2026-08-25T18:41:53Z

Content type: tutorial

Language: en

Sources: [select \* from depesz;](<https://devfeed.tech/sources/select-from-depesz.md>)

Topics: [PostgreSQL](<https://devfeed.tech/topics/postgresql.md>), [Databases](<https://devfeed.tech/topics/databases.md>), [test](<https://devfeed.tech/topics/test.md>)

Tags: [expression](<https://devfeed.tech/tags/expression.md>), [extension](<https://devfeed.tech/tags/extension.md>), [extensions](<https://devfeed.tech/tags/extensions.md>), [pg-re2](<https://devfeed.tech/tags/pg-re2.md>), [pg-tre](<https://devfeed.tech/tags/pg-tre.md>), [postgresql](<https://devfeed.tech/tags/postgresql.md>), [re2](<https://devfeed.tech/tags/re2.md>), [regexp](<https://devfeed.tech/tags/regexp.md>), [regular](<https://devfeed.tech/tags/regular.md>), [regular-expressions](<https://devfeed.tech/tags/regular-expressions.md>), [test-data](<https://devfeed.tech/tags/test-data.md>), [uncategorized](<https://devfeed.tech/tags/uncategorized.md>)

### AI overview

This article compares PostgreSQL regular-expression approaches using pg_tre and pg_re2 against built-in matching and pg_trgm. Tests on a large table of query plans find that pg_tre is slower than pg_trgm for exact substring searches but supports fuzzy matching, while pg_re2 performs faster than the tested built-in scan. The author notes that both extensions have limitations and rough edges.

### Source excerpt

Well, truth be told these are not all that new (couple of months), but I finally have gotten around to research it. So, let's see what's what. For starters I need some test data. Luckily, I have explain.depesz.com DB... Extracted all plans to side table, with this structure: =$ \d all_plans Table "public.all_plans" Column | ... Continue reading "New things for regular expressions in PostgreSQL (pg_tre and pg_re2)"

## Designing a custom AI agent for repetitive QA workflows

DevFeed: [Designing a custom AI agent for repetitive QA workflows](<https://devfeed.tech/articles/designing-a-custom-ai-agent-for-repetitive-qa-workflows-22590.md>)

Original publisher: [Read original article](<https://medium.com/amex-gbt-technology/designing-a-custom-ai-agent-for-repetitive-qa-workflows-0eee8dd0f267?source=rss----60a0578f4096---4>)

Author: Rimple Sharma

Published: 2026-05-13T09:34:47Z

Content type: tutorial

Language: en

Sources: [Amex GBT Technology](<https://devfeed.tech/sources/amex-gbt-technology.md>)

Topics: [AI Agent](<https://devfeed.tech/topics/ai-agent.md>), [Automation](<https://devfeed.tech/topics/automation.md>), [test](<https://devfeed.tech/topics/test.md>), [test data](<https://devfeed.tech/topics/test-data.md>), [configuration](<https://devfeed.tech/topics/configuration.md>), [pull-requests](<https://devfeed.tech/topics/pull-requests.md>), [consistency](<https://devfeed.tech/topics/consistency.md>)

Tags: [ai-agent](<https://devfeed.tech/tags/ai-agent.md>), [ai-skills](<https://devfeed.tech/tags/ai-skills.md>), [automation](<https://devfeed.tech/tags/automation.md>), [configuration](<https://devfeed.tech/tags/configuration.md>), [consistency](<https://devfeed.tech/tags/consistency.md>), [pull-requests](<https://devfeed.tech/tags/pull-requests.md>), [qa](<https://devfeed.tech/tags/qa.md>), [software-testing](<https://devfeed.tech/tags/software-testing.md>), [test-automation](<https://devfeed.tech/tags/test-automation.md>), [test-data](<https://devfeed.tech/tags/test-data.md>)

### AI overview

This article defines a repetitive QA workflow involving configuration updates, test-data additions, mapping checks, coverage validation, and pull requests. It argues that the main bottleneck is contextual decision-making and cross-file validation, which motivates designing a custom AI agent.

### Source excerpt

Part 1: Core problem definition, three pillars of an effective agent & why structured instructions matter.Source: AI generated image Engineers on QA teams spend a disproportionate share of their time on work that follows a consistent pattern: updating configurations, modifying test artifacts, executing focused validations, and managing pull requests. The tasks are well-defined but the repetition adds up fast. Individually, none of this is complicated. But taken together, these tasks are: Repetitive Error-prone Hard to repeat reliably During my time in automation, I kept running into the same problem. Every release brought the same requirements. New datasets had to be added so the test suite could cover the scenarios tied to them. It was never a one-time effort. The same work had to be repeated across different combinations, every single time. The process typically looked like this: 1. Updating multiple configuration files. 2. Adding the corresponding test data. 3. Making sure everything was mapped correctly. 4. Validating coverage and consistency. 5. Committing the changes and raising a PR. Each step on its own was straightforward. But strung together and repeated across releases, it consumed a meaningful chunk of time that could have gone elsewhere. Problem breakdownFig 2.0 Pain of manual repetitive process (Source: AI generated image) Each step is straightforward. But together, context switching between files, making manual edits, double checking mappings, it added up to 30 to 60 minutes per release cycle in our case. Miss one mapping, introduce a typo, and the build breaks. It wasn't hard work, just repetitive. And that's exactly the kind of work that makes test suites brittle over time. Even with automation in place, every iteration still required someone to identify what had changed, figure out which files were affected, and make sure everything stayed consistent across the board. The framework we had was solid. Scripts handled the heavy lifting well. But there

## The best way to clean up test data with Spring and Hibernate

DevFeed: [The best way to clean up test data with Spring and Hibernate](<https://devfeed.tech/articles/the-best-way-to-clean-up-test-data-with-spring-and-hibernate-21982.md>)

Original publisher: [Read original article](<https://vladmihalcea.com/clean-up-test-data-spring/>)

Author: vladmihalcea

Published: 2025-11-11T08:05:24Z

Content type: tutorial

Language: en

Sources: [Vlad Mihalcea](<https://devfeed.tech/sources/vlad-mihalcea.md>)

Topics: [Spring Boot](<https://devfeed.tech/topics/spring-boot.md>), [Integration testing](<https://devfeed.tech/topics/integration-testing.md>), [Testing](<https://devfeed.tech/topics/testing.md>), [Java](<https://devfeed.tech/topics/java.md>), [Spring Framework](<https://devfeed.tech/topics/spring-framework.md>)

Tags: [cleanup](<https://devfeed.tech/tags/cleanup.md>), [hibernate](<https://devfeed.tech/tags/hibernate.md>), [integration-testing](<https://devfeed.tech/tags/integration-testing.md>), [java](<https://devfeed.tech/tags/java.md>), [jpa](<https://devfeed.tech/tags/jpa.md>), [schema](<https://devfeed.tech/tags/schema.md>), [spring](<https://devfeed.tech/tags/spring.md>), [spring-boot](<https://devfeed.tech/tags/spring-boot.md>), [test-data](<https://devfeed.tech/tags/test-data.md>), [testing](<https://devfeed.tech/tags/testing.md>), [truncatemappedobjects](<https://devfeed.tech/tags/truncatemappedobjects.md>)

### AI overview

This tutorial examines how to clean up test data in Spring and Hibernate integration tests. It argues that relying on @DataJpaTest for automatic transaction rollback is not always appropriate and discusses limitations of its SQL logging, including its inability to show bind parameter values or indicate whether batching is used.

### Source excerpt

Introduction In this article, I'm going to show you the best way to clean up test data when using Spring and Hibernate. While it's very common to use the @DataJpaTest annotation when implementing integration tests, in this blog post, you will see why you are better off avoiding using this annotation. Why I don't use @DataJpaTest As explained by the manual, Spring Boot provides the @DataJpaTest annotation for Spring Data JPA integration testing. Once the @DataJpaTest annotation is added to an integration test, Spring Boot will make the following changes to the... Read More The post The best way to clean up test data with Spring and Hibernate appeared first on Vlad Mihalcea.

## The Performance of Various To-Many Nesting Algorithms

DevFeed: [The Performance of Various To-Many Nesting Algorithms](<https://devfeed.tech/articles/the-performance-of-various-to-many-nesting-algorithms-28965.md>)

Original publisher: [Read original article](<https://blog.jooq.org/the-performance-of-various-to-many-nesting-algorithms/>)

Author: lukaseder

Published: 2022-06-09T10:15:50Z

Content type: article

Language: en

Sources: [jOOQ](<https://devfeed.tech/sources/jooq.md>)

Topics: [Benchmark](<https://devfeed.tech/topics/benchmark.md>), [SQL](<https://devfeed.tech/topics/sql.md>), [Databases](<https://devfeed.tech/topics/databases.md>), [Object-relational mapping](<https://devfeed.tech/topics/orm.md>)

Tags: [benchmark](<https://devfeed.tech/tags/benchmark.md>), [benchmarks](<https://devfeed.tech/tags/benchmarks.md>), [database](<https://devfeed.tech/tags/database.md>), [java](<https://devfeed.tech/tags/java.md>), [jooq](<https://devfeed.tech/tags/jooq.md>), [jooq-development](<https://devfeed.tech/tags/jooq-development.md>), [json-arrayagg](<https://devfeed.tech/tags/json-arrayagg.md>), [many-to-many](<https://devfeed.tech/tags/many-to-many.md>), [multiset](<https://devfeed.tech/tags/multiset.md>), [mysql](<https://devfeed.tech/tags/mysql.md>), [nested-collections](<https://devfeed.tech/tags/nested-collections.md>), [one-to-many](<https://devfeed.tech/tags/one-to-many.md>), [oracle](<https://devfeed.tech/tags/oracle.md>), [ordbms](<https://devfeed.tech/tags/ordbms.md>), [performance](<https://devfeed.tech/tags/performance.md>), [postgresql](<https://devfeed.tech/tags/postgresql.md>), [sql](<https://devfeed.tech/tags/sql.md>), [sql-json](<https://devfeed.tech/tags/sql-json.md>), [sql-server](<https://devfeed.tech/tags/sql-server.md>), [sql-xml](<https://devfeed.tech/tags/sql-xml.md>), [test-data](<https://devfeed.tech/tags/test-data.md>)

### AI overview

This article benchmarks several approaches to nesting to-many relationships with jOOQ, including MULTISET emulation, single joins with client-side deduplication, and multiple queries per nesting level. It reports that these approaches outperform the N+1 approach, with relative performance depending on data size and use case.

### Source excerpt

It's been a while since jOOQ 3.15 has been released with its revolutionary standard SQL MULTISET emulation feature. A thing that has been long overdue and which I promised on twitter a few times is to run a few benchmarks comparing the performance of various approaches to nesting to-many relationships with jOOQ. This article will ... Continue reading The Performance of Various To-Many Nesting Algorithms ->

## Simple Data Modeling with a Test Data Set

DevFeed: [Simple Data Modeling with a Test Data Set](<https://devfeed.tech/articles/simple-data-modeling-with-a-test-data-set-34569.md>)

Original publisher: [Read original article](<https://tapoueh.org/blog/2017/11/simple-data-modeling-with-a-test-data-set/>)

Author: Dimitri Fontaine PostgreSQL Major Contributor; Author

Published: 2017-11-27T15:23:44Z

Content type: tutorial

Language: en

Sources: [Dimitri Fontaine](<https://devfeed.tech/sources/dimitri-fontaine.md>)

Topics: [data-modeling](<https://devfeed.tech/topics/data-modeling.md>), [PostgreSQL](<https://devfeed.tech/topics/postgresql.md>), [test data](<https://devfeed.tech/topics/test-data.md>), [SQL](<https://devfeed.tech/topics/sql.md>)

Tags: [data-modeling](<https://devfeed.tech/tags/data-modeling.md>), [how-to](<https://devfeed.tech/tags/how-to.md>), [postgresql](<https://devfeed.tech/tags/postgresql.md>), [sql](<https://devfeed.tech/tags/sql.md>), [test-data](<https://devfeed.tech/tags/test-data.md>)

### AI overview

This tutorial explains how to develop and test a PostgreSQL database schema using SQL scripts, sample data, explicit transactions, and rollback. It demonstrates a forum-style schema populated with random data so the model can be refined interactively without affecting existing application code.

### Source excerpt

In How to Write SQL we saw how to write SQL queries as separate .sql files, and we learnt about using query parameters with the psql syntax for that (:variable, :'variable', and :"identifier"). For writing our database model, the same tooling is all we need. An important aspect of using psql is its capacity to provide immediate feedback, and we can also have that with modeling too.

## Problem with random test data

DevFeed: [Problem with random test data](<https://devfeed.tech/articles/problem-with-random-test-data-27273.md>)

Original publisher: [Read original article](<https://blog.pchudzik.com/201706/random-test-data/>)

Published: 2017-06-13T00:00:00Z

Content type: opinion

Language: en

Sources: [Paweł Chudzik](<https://devfeed.tech/sources/pawe-chudzik.md>)

Topics: [Testing](<https://devfeed.tech/topics/testing.md>), [data](<https://devfeed.tech/topics/data.md>), [Groovy](<https://devfeed.tech/topics/groovy.md>)

Tags: [business-logic](<https://devfeed.tech/tags/business-logic.md>), [data](<https://devfeed.tech/tags/data.md>), [groovy](<https://devfeed.tech/tags/groovy.md>), [object](<https://devfeed.tech/tags/object.md>), [test-data](<https://devfeed.tech/tags/test-data.md>), [testing](<https://devfeed.tech/tags/testing.md>), [tests](<https://devfeed.tech/tags/tests.md>)

### AI overview

The article explains why random test data can make tests hard to reproduce, understand, and maintain once domain objects contain business logic. It recommends using object factories to create valid, predictable test objects.

### Source excerpt

Some time ago I noticed new library in our code base - Random Beans which as the name suggests is a tool developed to easily create random data and random objects for testing purposes. Unfortunately, we used it in the wrong way. Here's how we backed up from the random test data to regain control over testing. Read more