Source Code-Based Unit Test Generation Dataset

#Code Generation #Unit Test Generation #Assertion Generation #Test Case Design #Unit Test Generation #Software Quality Assurance #Test Tool Development #Code Review

4569
0.3GB
JSON
CATL
MOBIUSI INC

Updated:2026-11-03

AI Analysis & Value Prop

This dataset pairs source code for functions or classes with descriptions of their expected behavior and corresponding unit test code. Examples cover test structure, framework conventions, and assertion writing, supporting model training to interpret code and generate tests that verify intended behavior. It is suited to code supervised fine-tuning, test-generation evaluation, and software quality tool development.

Dataset Insights

Sample Examples

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Technical Specifications

Field	Type	Description
file_name	string	File name
source_code	string	The function or class implementation to be tested.
unit_test_code	string	Unit test code that exercises the source code and checks its expected behavior using appropriate test structure and assertions.
expected_behavior	string	A description of the intended behavior and relevant cases the tests should cover.

Compliance Statement

Authorization Type	Proprietary - Commercial AI Training License (No Redistribution)
Commercial Use	Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization	No PII, no real company names, simulated scenarios follow industry standards
Compliance System	Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Frequently Asked Questions

What does the dataset contain?: Each sample includes source code for a function or class, a description of its expected behavior, and unit test code designed to verify that behavior.

Which training tasks does it support?: It supports code generation and code supervised fine-tuning, with a focus on unit test generation, test case design, and assertion generation. It can also be used to evaluate a model's ability to write tests from code and behavioral requirements.

Does the dataset specify a testing framework?: Samples may reflect relevant testing framework conventions, test structures, and assertion styles. Check the actual samples to confirm the languages and frameworks represented, and consider normalizing formats before integrating them into a training pipeline.

How can I access the dataset, and what are the licensing terms?: Check the dataset product page or the applicable delivery channel for access details. Permitted uses, licensing, and commercial terms are defined by the dataset's license and delivery documentation.

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Cite this Work

@dataset{Mobiusi2026,
  title={Source Code-Based Unit Test Generation Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/26e9bc426aa7f7f3459d17795621a959},
  urldate={2026-10-22},
  keywords={unit test generation dataset,code generation dataset,source code testing,automated testing,test case generation,code SFT,software testing data,unit test code},
  version={1.0}
}

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