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SE Radio 633: Itamar Friedman on Automated Testing with Generative AI

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Manage episode 439431740 series 215
Content provided by SE-Radio Team. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by SE-Radio Team or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

Itamar Friedman, the CEO and co-founder of CodiumAI, speaks with host Gregory M. Kapfhammer about how to use generative AI techniques to support automated software testing. Their discussion centers around the design and use of Cover-Agent, an open-source implementation of the automated test augmentation tool described in the Foundations of Software Engineering (FSE) paper entitled “Automated Unit Test Improvement using Large Language Models at Meta“ by Alshahwan et al. The episode explores how large-language models (LLMs) can aid testers by automatically generating test cases that increase the code coverage of an existing testing suite. They also investigate other automated testing topics, including how Cover-Agent compares to different LLM-based tools and the strengths and weaknesses of using LLM-based approaches in software testing.

  continue reading

1025 episodes

Artwork
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Manage episode 439431740 series 215
Content provided by SE-Radio Team. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by SE-Radio Team or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

Itamar Friedman, the CEO and co-founder of CodiumAI, speaks with host Gregory M. Kapfhammer about how to use generative AI techniques to support automated software testing. Their discussion centers around the design and use of Cover-Agent, an open-source implementation of the automated test augmentation tool described in the Foundations of Software Engineering (FSE) paper entitled “Automated Unit Test Improvement using Large Language Models at Meta“ by Alshahwan et al. The episode explores how large-language models (LLMs) can aid testers by automatically generating test cases that increase the code coverage of an existing testing suite. They also investigate other automated testing topics, including how Cover-Agent compares to different LLM-based tools and the strengths and weaknesses of using LLM-based approaches in software testing.

  continue reading

1025 episodes

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