AutomTest 3.0: An automated test-case generation tool from User Story processing powered with LLMs

Test-driven development (TDD) and Behavior-driven development (BDD) approaches address software development issues, proposing the creation of unit tests for each system component before implementing the code for the corresponding functionality. This approach results in an objective and compact solution. It ensures that the entire codebase is tested and enhances the overall quality of the software. However, the testing process can be time-consuming and resource-intensive. Some tools were proposed to address those issues, but they lack functionalities based on User Story in a TDD approach. In this context, we propose the AutomTest 3.0 tool, which facilitates unit test case generation from user stories prior to writing the code base related to the functionality. Built upon previous versions of AutomTest, this tool extends the other ones by including generative AI to power the creation of suggestions for methods the software under test should have. This tool creates test cases for Java using techniques such as equivalence class partitioning, natural language processing, and generative artificial intelligence. To evaluate the effectiveness of AutomTest 3.0, we conducted an exploratory study with software development professionals. Their feedback highlighted the tool’s utility in their daily work routines. AutomTest 3.0 demonstrated promising results in test case generation, scenario coverage, and speed advantages in test case creation. https://youtu.be/xoTrvhlfvu8

Authors

Publication Details

Published
2024-09-30
DOI
https://doi.org/10.5753/sbes.2024.3603
Citations
2
Primary Topic
Software Testing and Debugging Techniques
Type
article
Field-Weighted Citation Impact
0.97
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article

AutomTest 3.0: An automated test-case generation tool from User Story processing powered with LLMs

Joanna C. S. Santos, Paulo Maciel
2 citations
Software Testing and Debugging Techniques
0.97
article

AutomTest 3.0: An automated test-case generation tool from User Story processing powered with LLMs

Joanna C. S. Santos, Paulo Maciel
article en
2 citations

Abstract

Test-driven development (TDD) and Behavior-driven development (BDD) approaches address software development issues, proposing the creation of unit tests for each system component before implementing the code for the corresponding functionality. This approach results in an objective and compact solution. It ensures that the entire codebase is tested and enhances the overall quality of the software. However, the testing process can be time-consuming and resource-intensive. Some tools were proposed to address those issues, but they lack functionalities based on User Story in a TDD approach. In this context, we propose the AutomTest 3.0 tool, which facilitates unit test case generation from user stories prior to writing the code base related to the functionality. Built upon previous versions of AutomTest, this tool extends the other ones by including generative AI to power the creation of suggestions for methods the software under test should have. This tool creates test cases for Java using techniques such as equivalence class partitioning, natural language processing, and generative artificial intelligence. To evaluate the effectiveness of AutomTest 3.0, we conducted an exploratory study with software development professionals. Their feedback highlighted the tool’s utility in their daily work routines. AutomTest 3.0 demonstrated promising results in test case generation, scenario coverage, and speed advantages in test case creation. https://youtu.be/xoTrvhlfvu8

Openalex Percentile: Top 21%
Software Testing and Debugging Techniques
0.97
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