Codetown

Codetown ::: a software developer's community

AITP-NCFL October 2021 presenation: " AITP-NCFL October 2021 Presentation "5 Great Tips for Giving Great Presentations"

Event Details

Time: October 19, 2021 from 6:30pm to 8pm
Location: Zoom
Website or Map: https://aitp-ncfl.org/events
Event Type: presentation
Organized By: Michael Lucas
Latest Activity: Oct 15, 2021

Export to Outlook or iCal (.ics)

Event Description

For our October presentation, we are delighted to host Terry Martin-Back presenting "5 Great Tips for Giving Great Presentations".

The presentation will be held on Tuesday, October 19, 2021 from 7 to 8 PM via this Zoom meeting.

See full information here.

Comment Wall

Welcome to
Codetown

Sign Up
or Sign In

Or sign in with:

Happy 10th year, JCertif!

Notes

Welcome to Codetown!

Codetown is a social network. It's got blogs, forums, groups, personal pages and more! You might think of Codetown as a funky camper van with lots of compartments for your stuff and a great multimedia system, too! Best of all, Codetown has room for all of your friends.

When you create a profile for yourself you get a personal page automatically. That's where you can be creative and do your own thing. People who want to get to know you will click on your name or picture and…

Continue

Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.

View All

Looking for Jobs or Staff?

Check out the Codetown Jobs group.

Enjoy the site? Support Codetown with your donation.

InfoQ Reading List

Presentation: How to Build a Database Without a Server

Alex Seaton discusses the architecture of ArcticDB, a high-performance Python/C++ library that replaces traditional database servers with a thick-client model. He explains how to achieve atomicity on object storage through bottom-up writes and shares deep insights into conflict-free replicated data types (CRDTs). He also explores the pitfalls of clock drift and distributed locking.

By Alex Seaton

Meta Applies Mutation Testing with LLM to Improve Compliance Coverage

Meta applies large language models to mutation testing through its Automated Compliance Hardening system, generating targeted mutants and tests to improve compliance coverage, reduce overhead, and detect privacy and safety risks. The approach supports scalable, LLM-driven test generation and continuous compliance across Meta’s platforms.

By Leela Kumili