Tackling the Beast: How to Gradually
Upgrade a Legacy Code Base to PHP 7

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December

Presented by Ann Gaffigan (@anngaff)

Date: December 21, 2017
Time: 20:00 CST

18:00 PST, 3:00 CET (Dec 22), 2:00 GMT (Dec 22)
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Hypothetically speaking, what if you wanted to change all of the lightbulbs in your house to use LED bulbs, but your current wiring didn’t support LED bulbs? You would need to re-wire your house, which would take a long time. In the meantime, you wouldn’t have any working electricity. Is there a better way? What if there was an adapter that could transition LED to work with old wiring if necessary, or if the wiring was new, just work as usual? That’s a metaphor for how I figured out how to gradually upgrade a legacy (LAMP) code base to be compliant with PHP 7.0. Since PHP deprecated the MySQL extension functions as of PHP 5.5.0 and removed in 7.0, we needed to transition a LOT of code in a legacy system to use the modern MySQLi extension functions. In trying to figure out how to upgrade the code base without ceasing new development on the system, we decided to use an adapter database class to allow us to transition gradually. In this session, we’ll explain how the adapter class works and also the rules we put in place to ensure there was an end to the transition tunnel.

Ann Gaffigan

Ann Gaffigan

Ann Gaffigan is the CTO and partner at National Land Realty, a full-service real estate brokerage company specializing in farm, ranch, plantation, timber, and recreational land across the country. She was formerly the CTO of Land Pros Realty, which merged with National Land Realty in January 2016.

Ann spent the first decade of her career growing her web and systems development business, Gazelle Incorporated, after graduating from the University of Nebraska with her bachelor’s in computer science in 2004. Gazelle Inc. served dozens of clients all over the United States, ranging from small businesses that needed informational websites to larger non-profits and commercial businesses needing integrated membership and operations systems.

 

Refactoring Done Right

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November 2017

Presented by Brandon Savage (@brandonsavage)

Date: November 16, 2017
Time: 20:00 CST

18:00 PST, 3:00 CET (Nov 17), 2:00 GMT (Nov 17)
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Everybody talks about refactoring, but what’s the best way to actually refactor a part of your application? Come watch a live session where we’ll refactor a piece of code and come away with a well-designed solution. Along the way we’ll learn how to spot candidates for refactoring, and pitfalls to avoid.

Brandon Savage

Brandon Savage

 

Machine Learning Circa Minority Report

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October 2017

Presented by Kesha Williams (@KeshaUCI)

Date: October 19, 2017
Time: 20:00 CDT

18:00 PDT, 3:00 CEST (Oct 20), 2:00 BST (Oct 20)
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Minority Report was a 2002 American science fiction film based in 2054 where police officers apprehended criminals based on predictions and foreknowledge. We are not in 2054 but fast-forward to 2017, we are now closer than ever before to the world imagined in Minority Report because of Machine Learning (ML). ML is a type of Artificial Intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. For all intents and purposes, ML is foreknowledge that can be applied across several disciplines in order to answer questions and make predictions. One such discipline, predictive policing, uses ML to predict the likelihood of crime. This talk introduces ML through a predictive policing program called SAM (Suspicious Activity Monitor). During this talk, the “secrets” and technologies behind SAM are uncovered and attendees walk away with the necessary tools and understanding to incorporate ML into their own applications.

Kesha Williams

Kesha Williams

Kesha Williams is a software engineer with over 20 years’ experience specializing in web application development. In addition to being a software engineer with Chick-fil-A, she trains and mentors thousands of software developers in the US, Europe, and Asia while teaching at the University of California. She’s authored courses on Java, Machine Learning (ML), Artificial Intelligence (AI), and Augmented Reality (AR). She most recently won the Think Different Innovation Award from Chick-fil-A for her work on investigating how emerging technologies like Artificial Intelligence (AI), Augmented Reality (AR), Computer Vision/Facial Recognition, and the Internet of Things (IOT) can enhance restaurant operations and customer experiences. She has worked for companies like Delta Air Lines, McKesson Information Systems, and Keane Federal Systems (U.S. Air Force), serving in various technical lead and software development roles. She did her summer internship with the National Security Agency (NSA); how cool is that? In her spare time, she leads the Georgia chapter of Technovation, serves as a mentor with the New York Academy of Sciences, and conducts free Hour of Code sessions for children at her local library.

 

Zero to Hero: API Development!

September 2017

Presented by Matt Trask (@matthewtrask)

Date: September 21, 2017
Time: 20:00 CDT

18:00 PDT, 3:00 CEST (Sep 22), 2:00 BST (Sep 22)
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This meeting is over, but you can still purchase the video.

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Everyone these days wants an API for their business. But are we doing it in a way that will keep our developers and users sane for years to come? In this talk, we explore everything from versioning, HTTP status codes, pagination, testing and documentation, all of which will help you years down the road!

Matt Trask

Matt Trask

Matt is an API developer, open source and PHP community member, mentor, and cycling enthusiast. If he isnt crafting API’s, he is usually on one of Nashville’s beautiful greenways hammering away on his bike!

Demystifying Algorithmic Complexity

August 2017 – US

Presented by John Bafford (@jbafford)

Date: August 17, 2017
Time: 20:00 CDT

18:00 PDT, 3:00 CEST (Aug 18), 2:00 BST (Aug 18)
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This meeting is over, but you can still purchase the video.

Purchase Video

Complexity Theory. Big-O. Constant, linear, logarithmic, and quadratic time vs. space trade-offs. What does it actually mean when we say a function or an algorithm is efficient? How can we tell if we can do better? Join me, on this tour through a corner of computer science that few developers actively think about, and you’ll discover a new way of looking at code and thinking about problems.

John Bafford

John Bafford

John Bafford has built web applications with PHP and JavaScript since 1999. He enjoys working with open source software, hiking, and home brewing.