Northern Virginia Software Symposium - April 19 - 21, 2013 - No Fluff Just Stuff

Kenneth Kousen

Northern Virginia Software Symposium

Reston · April 19 - 21, 2013

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Kenneth Kousen

President, Kousen IT, Inc.

Ken Kousen is a Java Champion, several time JavaOne Rock Star, and a Grails Rock Star. He is the author of the Pragmatic Library books “Mockito Made Clear” and “Help Your Boss Help You,” the O'Reilly books “Kotlin Cookbook”, “Modern Java Recipes”, and “Gradle Recipes for Android”, and the Manning book “Making Java Groovy”. He also has recorded over a dozen video courses for the O'Reilly Learning Platform, covering topics related to Android, Spring, Java, Groovy, Grails, and Gradle.

His academic background include BS degrees in Mechanical Engineering and Mathematics from M.I.T., an MA and Ph.D. in Aerospace Engineering from Princeton, and an MS in Computer Science from R.P.I. He is currently President of Kousen IT, Inc., based in Connecticut.

Presentations

Basic Android I

The basics of developing for the Android platform will be explored, from setting up the SDK to using the Android Studio IDE and the generated Gradle build files. No previous experience is required, other than a basic knowledge of Java.

Basic Android II

Building on the the previous talk, we'll add intents, customized layouts for alternative configurations, talk about the activity lifecycle, use logging, and more.

Testing Android Applications

Testing is well-established in the server-side Java ecosystem but is often an afterthought when it comes to Android development. This talk will review the available options and libraries used to do both unit and integration testing.

Bayes' Rule Says You'll Attend This Talk

Statistics is hot lately, due in part to the easy availability of large data sets and the successes of people like Nate Silver. These aren't your father's statistics, however. A quiet revolution has swept through the field, shifting it from traditional frequentist methods toward a more Bayesian approach. This talk will discuss Bayes' Theorem and show you how to do simple, back-of-the-envelope calculations to apply it to a wide variety of problems.