SE Radio 633: Itamar Friedman On Automated Testing With Generative AI Software Engineering Radio - The Podcast For Professional Software Developers podcast

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

2M ago 59:41

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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.

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998 episoder

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

Software Engineering Radio - the podcast for professional software developers

56,759 subscribers

published 2M ago

Del

MP3•Episoder hjem

Innhold levert av SE-Radio Team. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av SE-Radio Team eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.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

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