TestSpark: IntelliJ IDEA's Ultimate Test Generation Companion
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866914639616409600 |
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| author | Sapozhnikov, Arkadii Olsthoorn, Mitchell Panichella, Annibale Kovalenko, Vladimir Derakhshanfar, Pouria |
| author_facet | Sapozhnikov, Arkadii Olsthoorn, Mitchell Panichella, Annibale Kovalenko, Vladimir Derakhshanfar, Pouria |
| contents | Writing software tests is laborious and time-consuming. To address this, prior studies introduced various automated test-generation techniques. A well-explored research direction in this field is unit test generation, wherein artificial intelligence (AI) techniques create tests for a method/class under test. While many of these techniques have primarily found applications in a research context, existing tools (e.g., EvoSuite, Randoop, and AthenaTest) are not user-friendly and are tailored to a single technique. This paper introduces TestSpark, a plugin for IntelliJ IDEA that enables users to generate unit tests with only a few clicks directly within their Integrated Development Environment (IDE). Furthermore, TestSpark also allows users to easily modify and run each generated test and integrate them into the project workflow. TestSpark leverages the advances of search-based test generation tools, and it introduces a technique to generate unit tests using Large Language Models (LLMs) by creating a feedback cycle between the IDE and the LLM. Since TestSpark is an open-source (https://github.com/JetBrains-Research/TestSpark), extendable, and well-documented tool, it is possible to add new test generation methods into the plugin with the minimum effort. This paper also explains our future studies related to TestSpark and our preliminary results. Demo video: https://youtu.be/0F4PrxWfiXo |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_06580 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | TestSpark: IntelliJ IDEA's Ultimate Test Generation Companion Sapozhnikov, Arkadii Olsthoorn, Mitchell Panichella, Annibale Kovalenko, Vladimir Derakhshanfar, Pouria Software Engineering Writing software tests is laborious and time-consuming. To address this, prior studies introduced various automated test-generation techniques. A well-explored research direction in this field is unit test generation, wherein artificial intelligence (AI) techniques create tests for a method/class under test. While many of these techniques have primarily found applications in a research context, existing tools (e.g., EvoSuite, Randoop, and AthenaTest) are not user-friendly and are tailored to a single technique. This paper introduces TestSpark, a plugin for IntelliJ IDEA that enables users to generate unit tests with only a few clicks directly within their Integrated Development Environment (IDE). Furthermore, TestSpark also allows users to easily modify and run each generated test and integrate them into the project workflow. TestSpark leverages the advances of search-based test generation tools, and it introduces a technique to generate unit tests using Large Language Models (LLMs) by creating a feedback cycle between the IDE and the LLM. Since TestSpark is an open-source (https://github.com/JetBrains-Research/TestSpark), extendable, and well-documented tool, it is possible to add new test generation methods into the plugin with the minimum effort. This paper also explains our future studies related to TestSpark and our preliminary results. Demo video: https://youtu.be/0F4PrxWfiXo |
| title | TestSpark: IntelliJ IDEA's Ultimate Test Generation Companion |
| topic | Software Engineering |
| url | https://arxiv.org/abs/2401.06580 |