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Busting the Myths of Programmer Productivity

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Manage episode 279686474 series 1264075
Content provided by Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff 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://player.fm/legal.

Are the great programmers really 10 times faster than the rest? What does this difference in productivity even mean? What productivity distribution should we expect between professionals? How can we use this knowledge? In this webcast, we make the most of a large set of programmer training data using repeated measures to explore these questions.

What attendees will learn:

• For routine tasks, professional programmers have a narrower range of productivity than we first supposed, but almost half of the variation in individual productivity is noise, making programmer rankings suspect.

• Rather than finding the “fastest” programmers, we should find competent people and give them the training and environment they need to succeed.

  continue reading

147 episodes

Artwork
iconShare
 
Manage episode 279686474 series 1264075
Content provided by Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff 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://player.fm/legal.

Are the great programmers really 10 times faster than the rest? What does this difference in productivity even mean? What productivity distribution should we expect between professionals? How can we use this knowledge? In this webcast, we make the most of a large set of programmer training data using repeated measures to explore these questions.

What attendees will learn:

• For routine tasks, professional programmers have a narrower range of productivity than we first supposed, but almost half of the variation in individual productivity is noise, making programmer rankings suspect.

• Rather than finding the “fastest” programmers, we should find competent people and give them the training and environment they need to succeed.

  continue reading

147 episodes

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