Will AI Finally Make TDD Practical? | Diffblue’s Animesh Mishra

Dev Interrupted

Content provided by LinearB. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by LinearB 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://podcastplayer.com/legal.

1M ago 46:04

MP3•Episode home

The promise of Test Driven Development (or TDD) remains unfulfilled. Like many other forms of aspirational development, the practice has fallen victim to countless buzzword cycles. What if the answer is already in our toolbox?

This week, host Andrew Zigler sits down with Animesh Mishra, Senior Solutions Engineer at Diffblue, to unpack the gap between TDD's theoretical appeal and its practical challenges.

Animesh draws from his extensive experience to explain how deterministic AI can address the key challenges of building trust in AI for testing. These aren’t LLMs of today, but foundational machine learning models that can evaluate all possible branches of a piece of code to write test coverage for it. Imagine writing two years worth of tests for a legacy codebase… in two hours… with no errors!

If you enjoyed this conversation about the gaps between theory and execution in engineering culture, be sure to check out last week's chat with David Mytton about shift left adoption by engineering teams.

Check out:

Follow the hosts:

Follow Ben
Follow Andrew

Follow today's guest(s):

Support the show:

Subscribe to our Substack
Leave us a review
Subscribe on YouTube
Follow us on Twitter or LinkedIn

Offers:

Learn about Continuous Merge with gitStream
Get your DORA Metrics free forever

223 episodes

#Tech #LinearB #Development #Software #Software Development #Data #Agile #DevOps