Conference Papers Year : 2023

A Unit Test Metamodel for Test Generation

Abstract

Unit testing is a crucial aspect of software development, but developers often lack the time and resources to create comprehensive tests for their code. This can result in codebases that are vulnerable to bugs and issues. To address this problem, we present a unit test metamodel that enables the generation of unit tests. The metamodel provides a language-agnostic abstraction that enables automated transformation and code generation. We use the Famix family of models and tools from the Moose platform to build our metamodel and for code analysis. To generate realistic tests, we plan to use application traces consisting of method arguments and results. Our objective is to generate maintainable, human-readable tests that cover important use cases, including edge cases and rare scenarios. In this paper, we discuss related work in unit test generation, present the details of our metamodel, including its design, implementation and usage, and explore future work that will evaluate the effectiveness of our approach through case studies and experiments.
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hal-04219649 , version 1 (27-09-2023)

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  • HAL Id : hal-04219649 , version 1

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Gabriel Darbord, Anne Etien, Nicolas Anquetil, Benoît Verhaeghe, Mustapha Derras. A Unit Test Metamodel for Test Generation. International Workshop on Smalltalk Technologies, Stephane Ducasse; Gordana Rakic, Aug 2023, Lyon, France. ⟨hal-04219649⟩
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