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Programming

Google Play Services 5.0

Android Developers Blog - 7 hours 10 min ago
gps

Google Play services 5.0 is now rolled out to devices worldwide, and it includes a number of features you can use to improve your apps. This release introduces Android wearable services APIs, Dynamic Security Provider and App Indexing, whilst also including updates to the Google Play game services, Cast, Drive, Wallet, Analytics, and Mobile Ads.

Android wearable services

Google Play services 5.0 introduces a set of APIs that make it easier to communicate with your apps running on Android wearables. The APIs provide an automatically synchronized, persistent data store and a low-latency messaging interface that let you sync data, exchange control messages, and transfer assets.

Dynamic security provider

Provides an API that apps can use to easily install a dynamic security provider. The dynamic security provider includes a replacement for the platform's secure networking APIs, which can be updated frequently for rapid delivery of security patches. The current version includes fixes for recent issues identified in OpenSSL.

Google Play game services

Quests are a new set of APIs to run time-based goals for players, and reward them without needing to update the game. To do this, you can send game activity data to the Quests service whenever a player successfully wins a level, kills an alien, or saves a rare black sheep, for example. This tells Quests what’s going on in the game, and you can use that game activity to create new Quests. By running Quests on a regular basis, you can create an unlimited number of new player experiences to drive re-engagement and retention.

Saved games lets you store a player's game progress to the cloud for use across many screen, using a new saved game snapshot API. Along with game progress, you can store a cover image, description and time-played. Players never play level 1 again when they have their progress stored with Google, and they can see where they left off when you attach a cover image and description. Adding cover images and descriptions provides additional context on the player’s progress and helps drive re-engagement through the Play Games app.

App Indexing API

The App Indexing API provides a way for you to notify Google about deep links in your native mobile applications and drive additional user engagement. Integrating with the App Indexing API allows the Google Search app to serve up your app’s history to users as instant Search suggestions, providing fast and easy access to inner pages in your app. The deep links reported using the App Indexing API are also used by Google to index your app’s content and surface them as deep links to Google search result.

Google Cast

The Google Cast SDK now includes media tracks that introduce closed caption support for Chromecast.

Drive

The Google Drive API adds the ability to sort query results, create folders offline, and select any mime type in the file picker by default.

Wallet

Wallet objects from Google take physical objects (like loyalty cards, offers) from your wallet and store them in the cloud. In this release, Wallet adds "Save to Wallet" button support for offers. When a user clicks "Save to Wallet" the offer gets saved and shows up in the user's Google Wallet app. Geo-fenced in-store notifications prompt the user to show and scan digital cards at point-of-sale, driving higher redemption. This also frees the user from having to carry around offers and loyalty cards.

Users can also now use their Google Wallet Balance to pay for Instant Buy transactions by providing split tender support. With split tender, if your Wallet Balance is not sufficient, the payment is split between your Wallet Balance and a credit/debit card in your Google Wallet.

Analytics

Enhanced Ecommerce provides visibility into the full customer journey, adding the ability to measure product impressions, product clicks, viewing product details, adding a product to a shopping cart, initiating the checkout process, internal promotions, transactions, and refunds. Together they help users gain deeper insights into the performance of their business, including how far users progress through the shopping funnel and where they are abandoning in the purchase process. Enhanced Ecommerce also allows users to analyze the effectiveness of their marketing and merchandising efforts, including the impact of internal promotions, coupons, and affiliate marketing programs.

Mobile Ads

Google Mobile Ads are a great way to monetise your apps and you now have access to better in-app purchase ads. We've now added a default implementation for consumable purchases using the Google Play In-app Billing service.

And that’s another release of Google Play services. The updated Google Play services SDK is now available through the Android SDK manager. For details on the APIs, please see New Features in Google Play services 5.0.




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Categories: Programming

KNOX Contribution to Android: Accelerating Android in the Workplace

Android Developers Blog - 14 hours 32 min ago

Srikanth Rajagopalan, PM Director and Workplace aficionado

Recently at Google I/O, we announced a comprehensive set of new features that will allow IT organizations to easily deploy and manage Android devices in enterprise environments. These features will be built into the upcoming Android L release.

Samsung, with its KNOX technology, has been a thought leader in the enterprise mobility space. In order to accelerate Android adoption in the enterprise, we have partnered with Samsung to bring key KNOX functionality into Android, for the benefit of the entire Android ecosystem. We thank Samsung for their contributions. These new capabilities will make it easy for IT organizations to allow employees to bring their own Android devices to work (BYOD) and use them on the corporate network or to simply issue new Android devices to their employees. IT administrators will be able to manage a wide range of Android devices from many manufacturers, using third-party Enterprise Mobility Management (EMM) solutions that are built on top of the new enterprise APIs launching with Android L release.

Google and Samsung together designed the new enterprise APIs around three major concepts:

  • Device and data security
  • Support for IT policies and restrictions
  • Mobile application management
Device and data security

At the core of the expanded enterprise capabilities being introduced in Android ‘L’ lies a set of technologies that are designed to keep personal and corporate data both separate and safe. We achieve the data separation by building on the existing multi-user support in Android: personal and corporate applications will run as two separate Android users. Data is kept safe by using block-level disk encryption as well as verified boot technology. For those of you familiar with KNOX, this is analogous to KNOX Workspace. EMMs will be able to take advantage of new Android SDK APIs to enable the creation of a managed profile, which is where all corporate applications and data will reside.

Support for IT restrictions and policies

EMMs can use new Android SDK APIs , which have evolved from KNOX APIs, to allow IT admins to enforce a wide set of policies, ranging from system settings and certificate provisioning to application-specific (e.g. Chrome) configurations and restrictions.

Mobile application management

EMMs will be able to use new backend APIs, adapted from KNOX APIs and built around strong security principles for on-device app deployment, to allow IT admins to curate the corporate application catalog and to remotely deploy applications to the managed profile on the employees’ devices.

We encourage developers interested in the new Enterprise APIs to download and test the Android L Developer Preview. For developers who have already built applications using Samsung KNOX APIs, Samsung will be providing a KNOX Compatibility Library that will let such applications run on all Android L devices.

You can read more about this collaboration on the Samsung KNOX blog. Stay tuned for additional details.


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Categories: Programming

Who's Managing Your Company?

One of the best books I’m reading lately is The Future of Management, by Gary Hamel.

It’s all about how management innovation is the best competitive advantage, whether you look through the history of great businesses or the history of great militaries.  Hamel makes a great case that strategic innovation, product or service innovation, and operational innovation are fleeting advantages, but management innovation leads to competitive advantage for the long haul.

In The Future of Management, Hamel poses a powerful question …

“Who is managing your company?”

Via The Future of Management:

“Who's managing your company?  You might be tempted to answer, 'the CEO,' or 'the executive team,' or 'all of us in middle management.'  And you'd be right, but that wouldn't be the whole truth.  To a large extent, your company is being managed right now by a small coterie of long-departed theorists and practitioners who invented the rules and conventions of 'modern' management back in the early years of the 20th century.  They are the poltergeists who inhabit the musty machinery of management.  It is their edicts, echoing across the decades, that invisibly shape the way your company allocates resources, sets budgets, distributes power, rewards people, and makes decisions.”

That’s why it’s easy for CEOs to hop around companies …

Via The Future of Management:

“So pervasive is the influence of these patriarchs that the technology of management varies only slightly from firm to firm.  Most companies have a roughly similar management hierarchy (a cascade of EVPs, SVPs, and VPs).  They have analogous control systems, HR practices, and planning rituals, and rely on comparable reporting structures and review systems.  That's why it's so easy for a CEO to jump from one company to another -- the levers and dials of management are more or less the same in every corporate cockpit.”

What really struck me here is how much management approach has been handed down through the ages, and accepted as status quo.

It’s some great good for thought, especially given that management innovation is THE most powerful form of competitive advantage from an innovation standpoint (which Hamel really builds a strong case here throughout the entirety of the book.)

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Categories: Architecture, Programming

Why I am AGAINST Net Neutrality

No, I’m not saying this just to get a rise out of you, I am actually against net neutrality and here is why: Net neutrality is this principle that says internet service providers should treat all data on the internet equally. I actually like this idea; I agree with it; I hope internet providers choose […]

The post Why I am AGAINST Net Neutrality appeared first on Simple Programmer.

Categories: Programming

100 Articles to Sharpen Your Mind

Actually, it's more than 100 articles for your mind.  I've tagged my articles with "mind" on Sources of Insight that focus on increasing your "intellectual horsepower":

Articles on Mind Power and the Power of Thoughts

Here are a few of the top mind articles that you can quickly get results with:

Note that if reading faster is important to you, then I recommend also reading How To Read 10,000 Words a Minute (it’s my ultimate edge) and The Truth About Speed Reading.

If there’s one little trick I use with reading (whether it’s a book, an email, or whatever), I ask myself “what’s the insight?” or “what’s the action?” or “how can I use this?"  You’d be surprised but just asking yourself those little focusing questions can help you parse down cluttered content fast and find the needles in the haystack.

Categories: Architecture, Programming

R: ggplot – Plotting back to back bar charts

Mark Needham - Sun, 07/20/2014 - 17:50

I’ve been playing around with R’s ggplot library to explore the Neo4j London meetup and the next thing I wanted to do was plot back to back bar charts showing ‘yes’ and ‘no’ RSVPs.

I’d already done the ‘yes’ bar chart using the following code:

query = "MATCH (e:Event)<-[:TO]-(response {response: 'yes'})
         RETURN response.time AS time, e.time + e.utc_offset AS eventTime"
allYesRSVPs = cypher(graph, query)
allYesRSVPs$time = timestampToDate(allYesRSVPs$time)
allYesRSVPs$eventTime = timestampToDate(allYesRSVPs$eventTime)
allYesRSVPs$difference = as.numeric(allYesRSVPs$eventTime - allYesRSVPs$time, units="days")
 
ggplot(allYesRSVPs, aes(x=difference)) + geom_histogram(binwidth=1, fill="green")
2014 07 20 01 15 39

The next step was to create a similar thing for people who’d RSVP’d ‘no’ having originally RSVP’d ‘yes’ i.e. people who dropped out:

query = "MATCH (e:Event)<-[:TO]-(response {response: 'no'})<-[:NEXT]-()
         RETURN response.time AS time, e.time + e.utc_offset AS eventTime"
allNoRSVPs = cypher(graph, query)
allNoRSVPs$time = timestampToDate(allNoRSVPs$time)
allNoRSVPs$eventTime = timestampToDate(allNoRSVPs$eventTime)
allNoRSVPs$difference = as.numeric(allNoRSVPs$eventTime - allNoRSVPs$time, units="days")
 
ggplot(allNoRSVPs, aes(x=difference)) + geom_histogram(binwidth=1, fill="red")
2014 07 20 17 25 03

As expected if people are going to drop out they do so a day or two before the event happens. By including the need for a ‘NEXT’ relationship we only capture the people who replied ‘yes’ and changed it to ‘no’. We don’t capture the people who said ‘no’ straight away.

I thought it’d be cool to be able to have the two charts back to back using the same scale so I could compare them against each other which led to my first attempt:

yes = ggplot(allYesRSVPs, aes(x=difference)) + geom_histogram(binwidth=1, fill="green")
no = ggplot(allNoRSVPs, aes(x=difference)) + geom_histogram(binwidth=1, fill="red") + scale_y_reverse()
library(gridExtra)
grid.arrange(yes,no,ncol=1,widths=c(1,1))

scale_y_reverse() flips the y axis so we’d see the ‘no’ chart upside down. The last line plots the two charts in a grid containing 1 column which forces them to go next to each other vertically.

2014 07 20 17 29 27

When we compare them next to each other we can see that the ‘yes’ replies are much more spread out whereas if people are going to drop out it nearly always happens a week or so before the event happens. This is what we thought was happening but it’s cool to have it confirmed by the data.

One annoying thing about that visualisation is that the two charts aren’t on the same scale. The ‘no’ chart only goes up to 100 days whereas the ‘yes’ one goes up to 120 days. In addition, the top end of the ‘yes’ chart is around 200 whereas the ‘no’ is around 400.

Luckily we can solve that problem by fixing the axes for both plots:

yes = ggplot(allYesRSVPs, aes(x=difference)) + 
  geom_histogram(binwidth=1, fill="green") +
  xlim(0,120) + 
  ylim(0, 400)
 
no = ggplot(allNoRSVPs, aes(x=difference)) +
  geom_histogram(binwidth=1, fill="red") +
  xlim(0,120) + 
  ylim(0, 400) +
  scale_y_reverse()

Now if we re-render it looks much better:

2014 07 20 17 42 40

From having comparable axes we can see that a lot more people drop out of an event (500) as it approaches than new people sign up (300). This is quite helpful for working out how many people are likely to show up.

We’ve found that the number of people RSVP’d ‘yes’ to an event will drop by 15-20% overall from 2 days before an event up until the evening of the event and the data seems to confirm this.

The only annoying thing about this approach is that the axes are repeated due to them being completely separate charts.

I expect it would look better if I can work out how to combine the two data frames together and then pull out back to back charts based on a variable in the combined data frame.

I’m still working on that so suggestions are most welcome. The code is on github if you want to play with it.

Categories: Programming

Neo4j 2.1.2: Finding where I am in a linked list

Mark Needham - Sun, 07/20/2014 - 16:13

I was recently asked how to calculate the position of a node in a linked list and realised that as the list increases in size this is one of the occasions when we should write an unmanaged extension rather than using cypher.

I wrote a quick bit of code to create a linked list with 10,000 elements in it:

public class Chains 
{
    public static void main(String[] args)
    {
        String simpleChains = "/tmp/longchains";
        populate( simpleChains, 10000 );
    }
 
    private static void populate( String path, int chainSize )
    {
        GraphDatabaseService db = new GraphDatabaseFactory().newEmbeddedDatabase( path );
        try(Transaction tx = db.beginTx()) {
            Node currentNode = null;
            for ( int i = 0; i < chainSize; i++ )
            {
                Node node = db.createNode();
 
                if(currentNode != null) {
                    currentNode.createRelationshipTo( node, NEXT );
                }
                currentNode = node;
            }
            tx.success();
        }
 
 
        db.shutdown();
    }
}

To find our distance from the end of the linked list we could write the following cypher query:

match n  where id(n) = {nodeId}  with n 
match path = (n)-[:NEXT*]->() 
RETURN id(n) AS nodeId, length(path) AS length 
ORDER BY length DESC 
LIMIT 1;

For simplicity we’re finding a node by it’s internal node id and then finding the ‘NEXT’ relationships going out from this node recursively. We then filter the results so that we only get the longest path back which will be our distance to the end of the list.

I noticed that this query would sometimes take 10s of seconds so I wrote a version using the Java Traversal API to see whether I could get it any quicker.

This is the Java version:

try(Transaction tx = db.beginTx()) {
    Node startNode = db.getNodeById( nodeId );
    TraversalDescription traversal = db.traversalDescription();
    Traverser traverse = traversal
            .depthFirst()
            .relationships( NEXT, Direction.OUTGOING )
            .sort( new Comparator<Path>()
            {
                @Override
                public int compare( Path o1, Path o2 )
                {
                    return Integer.valueOf( o2.length() ).compareTo( o1 .length() );
                }
            } )
            .traverse( startNode );
 
    Collection<Path> paths = IteratorUtil.asCollection( traverse );
 
    int maxLength = traverse.iterator().next().length();
    System.out.print( maxLength );
 
    tx.failure();
}

This is a bit more verbose than the cypher version but computes the same result. We’ve sorted the paths by length using a comparator to ensure we get the longest path back first.

I created a little program to warm up the caches and kick off a few iterations where I queried from different nodes and returned the length and time taken. These were the results:

--------
(Traversal API) Node:    1, Length: 9998, Time (ms):  15
       (Cypher) Node:    1, Length: 9998, Time (ms): 26225
(Traversal API) Node:  456, Length: 9543, Time (ms):  10
       (Cypher) Node:  456, Length: 9543, Time (ms): 24881
(Traversal API) Node:  761, Length: 9238, Time (ms):   9
       (Cypher) Node:  761, Length: 9238, Time (ms): 9941
--------
(Traversal API) Node:    1, Length: 9998, Time (ms):   9
       (Cypher) Node:    1, Length: 9998, Time (ms): 12537
(Traversal API) Node:  456, Length: 9543, Time (ms):   8
       (Cypher) Node:  456, Length: 9543, Time (ms): 15690
(Traversal API) Node:  761, Length: 9238, Time (ms):   7
       (Cypher) Node:  761, Length: 9238, Time (ms): 9202
--------
(Traversal API) Node:    1, Length: 9998, Time (ms):   8
       (Cypher) Node:    1, Length: 9998, Time (ms): 11905
(Traversal API) Node:  456, Length: 9543, Time (ms):   7
       (Cypher) Node:  456, Length: 9543, Time (ms): 22296
(Traversal API) Node:  761, Length: 9238, Time (ms):   8
       (Cypher) Node:  761, Length: 9238, Time (ms): 8739
--------

Interestingly when I reduced the size of the linked list to 1000 the difference wasn’t so pronounced:

--------
(Traversal API) Node:    1, Length: 998, Time (ms):   5
       (Cypher) Node:    1, Length: 998, Time (ms): 174
(Traversal API) Node:  456, Length: 543, Time (ms):   2
       (Cypher) Node:  456, Length: 543, Time (ms):  71
(Traversal API) Node:  761, Length: 238, Time (ms):   1
       (Cypher) Node:  761, Length: 238, Time (ms):  13
--------
(Traversal API) Node:    1, Length: 998, Time (ms):   2
       (Cypher) Node:    1, Length: 998, Time (ms): 111
(Traversal API) Node:  456, Length: 543, Time (ms):   1
       (Cypher) Node:  456, Length: 543, Time (ms):  40
(Traversal API) Node:  761, Length: 238, Time (ms):   1
       (Cypher) Node:  761, Length: 238, Time (ms):  12
--------
(Traversal API) Node:    1, Length: 998, Time (ms):   3
       (Cypher) Node:    1, Length: 998, Time (ms): 129
(Traversal API) Node:  456, Length: 543, Time (ms):   2
       (Cypher) Node:  456, Length: 543, Time (ms):  48
(Traversal API) Node:  761, Length: 238, Time (ms):   0
       (Cypher) Node:  761, Length: 238, Time (ms):  12
--------

which is good news as most linked lists that we’ll create will be in the 10s – 100s range rather than 10,000 which was what I was faced with.

I’m sure cypher will reach parity for this type of query in future which will be great as I like writing cypher much more than I do Java. For now though it’s good to know we have a backup option to call on when necessary.

The code is available as a gist if you want to play around with it further.

Categories: Programming

R: ggplot – Don’t know how to automatically pick scale for object of type difftime – Discrete value supplied to continuous scale

Mark Needham - Sun, 07/20/2014 - 01:21

While reading ‘Why The R Programming Language Is Good For Business‘ I came across Udacity’s ‘Data Analysis with R‘ courses – part of which focuses exploring data sets using visualisations, something I haven’t done much of yet.

I thought it’d be interesting to create some visualisations around the times that people RSVP ‘yes’ to the various Neo4j events that we run in London.

I started off with the following query which returns the date time that people replied ‘Yes’ to an event and the date time of the event:

library(Rneo4j)
query = "MATCH (e:Event)<-[:TO]-(response {response: 'yes'})
         RETURN response.time AS time, e.time + e.utc_offset AS eventTime"
allYesRSVPs = cypher(graph, query)
allYesRSVPs$time = timestampToDate(allYesRSVPs$time)
allYesRSVPs$eventTime = timestampToDate(allYesRSVPs$eventTime)
 
> allYesRSVPs[1:10,]
                  time           eventTime
1  2011-06-05 12:12:27 2011-06-29 18:30:00
2  2011-06-05 14:49:04 2011-06-29 18:30:00
3  2011-06-10 11:22:47 2011-06-29 18:30:00
4  2011-06-07 15:27:07 2011-06-29 18:30:00
5  2011-06-06 20:21:45 2011-06-29 18:30:00
6  2011-07-04 19:49:04 2011-07-27 19:00:00
7  2011-07-05 16:40:10 2011-07-27 19:00:00
8  2011-08-19 07:41:10 2011-08-31 18:30:00
9  2011-08-24 12:47:40 2011-08-31 18:30:00
10 2011-08-18 09:56:53 2011-08-31 18:30:00

I wanted to create a bar chart showing the amount of time in advance of a meetup that people RSVP’d ‘yes’ so I added the following column to my data frame:

allYesRSVPs$difference = allYesRSVPs$eventTime - allYesRSVPs$time
 
> allYesRSVPs[1:10,]
                  time           eventTime    difference
1  2011-06-05 12:12:27 2011-06-29 18:30:00 34937.55 mins
2  2011-06-05 14:49:04 2011-06-29 18:30:00 34780.93 mins
3  2011-06-10 11:22:47 2011-06-29 18:30:00 27787.22 mins
4  2011-06-07 15:27:07 2011-06-29 18:30:00 31862.88 mins
5  2011-06-06 20:21:45 2011-06-29 18:30:00 33008.25 mins
6  2011-07-04 19:49:04 2011-07-27 19:00:00 33070.93 mins
7  2011-07-05 16:40:10 2011-07-27 19:00:00 31819.83 mins
8  2011-08-19 07:41:10 2011-08-31 18:30:00 17928.83 mins
9  2011-08-24 12:47:40 2011-08-31 18:30:00 10422.33 mins
10 2011-08-18 09:56:53 2011-08-31 18:30:00 19233.12 mins

I then tried to use ggplot to create a bar chart of that data:

> ggplot(allYesRSVPs, aes(x=difference)) + geom_histogram(binwidth=1, fill="green")

Unfortunately that resulted in this error:

Don't know how to automatically pick scale for object of type difftime. Defaulting to continuous
Error: Discrete value supplied to continuous scale

I couldn’t find anyone who had come across this problem before in my search but I did find the as.numeric function which seemed like it would put the difference into an appropriate format:

allYesRSVPs$difference = as.numeric(allYesRSVPs$eventTime - allYesRSVPs$time, units="days")
> ggplot(allYesRSVPs, aes(x=difference)) + geom_histogram(binwidth=1, fill="green")

that resulted in the following chart:

2014 07 20 01 15 39

We can see there is quite a heavy concentration of people RSVPing yes in the few days before the event and then the rest are scattered across the first 30 days.

We usually announce events 3/4 weeks in advance so I don’t know that it tells us anything interesting other than that it seems like people sign up for events when an email is sent out about them.

The date the meetup was announced (by email) isn’t currently exposed by the API but hopefully one day it will be.

The code is on github if you want to have a play – any suggestions welcome.

Categories: Programming

Episode 206: Ken Collier on Agile Analytics

Johannes Thönes talks to Dr. Ken Collier, Director of Agile Analytics at ThoughtWorks about Agile Analytics. The outline includes: descriptive analytics, predictive analytic and prescriptive analytics; artificial intelligence, machine learning, data mining and statistics; collaborative filtering; data science and data scientists; data warehousing and business intelligence; online analytical processing (OLAP), extract transform load (ETL), feature […]
Categories: Programming

Porting Your Android Wear Developer Preview Code to the Latest Support Library

Android Developers Blog - Fri, 07/18/2014 - 01:18

Today’s post on #AndroidWear is from +Wayne Piekarski.

Now that the full Android Wear SDK is available, it’s time to port your existing wearable-enabled notification code from the Developer Preview. In the process, you’ll switch to using the latest Android support library, and there are some small API changes that will require you to update your code. This article will show you how to update my previous code samples that were released earlier for stacks and pages, which you can use to guide the conversion of your own code as well.

To get started with an existing project in Android Studio, you should update to the 0.8 or later release. You also need to make sure you’ve downloaded the Google Support Library version 20 or later from the SDK Manager. Since this is only a notification-based example, there’s no need to download the full Android Wear SDK, which is only needed if you want to create an APK to run on the wearable device.

Unix diff output is used to show the necessary changes in an easy to understand way. Do not copy the + or - symbols at the start of each line, and ignore the lines starting with @@ which are used to indicate the line number that changed. For the curious, I used the following command to generate the diff output from the last commit in my GIT repository (the -U1 shows one line of context to keep the output simple):

git show HEAD -U1

Gradle changes

To add the new support-v4 library, you need to edit your build.gradle file like so:

@@ -24,2 +24,3 @@ dependencies {
     compile 'com.android.support:appcompat-v7:19.+'
+    compile 'com.android.support:support-v4:20.0+'
 }

Make sure you remove the wearable-preview-support.jar that was provided with the Developer Preview from your libs directory and build.gradle file, since these features are now in the standard support library.

Package imports

Since the APIs and package names have changed, the import statements at the top of MainActivity.java need to be adjusted like this:

@@ -7,3 +7,2 @@ import android.view.MenuItem;
-import android.support.v4.app.NotificationCompat;
 import android.app.Notification;
@@ -13,4 +12,9 @@ import android.graphics.Bitmap;
 import android.graphics.BitmapFactory;
-import android.preview.support.v4.app.NotificationManagerCompat;
-import android.preview.support.wearable.notifications.WearableNotifications;
+import android.support.v4.app.NotificationCompat;
+import android.support.v4.app.NotificationManagerCompat;
+
+// Extra dependencies needed for the pages example
+import java.util.ArrayList;
+import java.util.List;
+import android.support.v4.app.NotificationCompat.BigTextStyle;
Stacking notifications

Since the preview SDK, we have simplified how notifications are implemented. The existing NotificationCompat.Builder() was extended to support groups directly, instead of a separate WearableNotifications class. The steps are a lot simpler, as can be seen with the following changes to showStackNotifications():

@@ -63,3 +67,3 @@ public class MainActivity extends ActionBarActivity {
         // Group notification that will be visible on the phone
-    NotificationCompat.Builder builderG = new NotificationCompat.Builder(this)
+    Notification summaryNotification = new NotificationCompat.Builder(this)
             .setContentTitle("2 Pet Notifications")
@@ -67,5 +71,5 @@ public class MainActivity extends ActionBarActivity {
             .setSmallIcon(R.drawable.ic_launcher)
-                .setLargeIcon(bitmapMila);
-    Notification summaryNotification = new WearableNotifications.Builder(builderG)
-            .setGroup(GROUP_KEY_MESSAGES, WearableNotifications.GROUP_ORDER_SUMMARY)
+                .setLargeIcon(bitmapMila)
+            .setGroup(GROUP_KEY_MESSAGES)
+            .setGroupSummary(true)
             .build();
@@ -76,3 +80,3 @@ public class MainActivity extends ActionBarActivity {
             PendingIntent.getActivity(this, notificationId+1, viewIntent1, 0);
-    NotificationCompat.Builder builder1 = new NotificationCompat.Builder(this)
+    Notification notification1 = new NotificationCompat.Builder(this)
             .addAction(R.drawable.ic_action_done, "Treat Fed", viewPendingIntent1)
@@ -81,4 +85,3 @@ public class MainActivity extends ActionBarActivity {
                     + "Can we have steak?")
-                .setSmallIcon(R.drawable.ic_launcher);
-    Notification notification1 = new WearableNotifications.Builder(builder1)
+            .setSmallIcon(R.drawable.ic_launcher)
             .setGroup(GROUP_KEY_MESSAGES)
@@ -89,3 +92,3 @@ public class MainActivity extends ActionBarActivity {
             PendingIntent.getActivity(this, notificationId+2, viewIntent2, 0);
-    NotificationCompat.Builder builder2 = new NotificationCompat.Builder(this)
+    Notification notification2 = new NotificationCompat.Builder(this)
             .addAction(R.drawable.ic_action_done, "Water Filled", viewPendingIntent2)
@@ -93,4 +96,3 @@ public class MainActivity extends ActionBarActivity {
             .setContentText("Can you refill our water bowl?")
-            .setSmallIcon(R.drawable.ic_launcher);
-        Notification notification2 = new WearableNotifications.Builder(builder2)
+            .setSmallIcon(R.drawable.ic_launcher)
             .setGroup(GROUP_KEY_MESSAGES)
Page notifications

Page notifications have also changed to use a WearableExtender() class instead of the WearableNotifications class, as can be seen here in showPageNotifications():

@@ -151,3 +153,3 @@ public class MainActivity extends ActionBarActivity {
             PendingIntent.getActivity(this, notificationId+1, viewIntent1, 0);
-    NotificationCompat.Builder builder1 = new NotificationCompat.Builder(this)
+    Notification notification1 = new NotificationCompat.Builder(this)
             .addAction(R.drawable.ic_action_done, "Returned", viewPendingIntent1)
@@ -155,5 +157,4 @@ public class MainActivity extends ActionBarActivity {
             .setContentText("You have " + numOverdue + " books due at the library")
-            .setSmallIcon(R.drawable.ic_launcher);
-    Notification notification1 = new WearableNotifications.Builder(builder1)
-            .addPages(extras)
+                .setSmallIcon(R.drawable.ic_launcher)
+            .extend(new NotificationCompat.WearableExtender().addPages(extras))
             .build();
Conclusion

If you want to download the final source code of showStackNotifications() and showPageNotifications(), you can download the MainActivity.java file. You can build this file easily by creating a new project in Android Studio, adding the support library, and then copying in this MainActivity.java.

As you can see, porting this previous code over to the latest Android Wear SDK is really easy! It should take you hardly any time at all to get your experimental applications ported over and ready for publishing on the Google Play!


Join the discussion on
+Android Developers


Categories: Programming

The "Just In Time" Theory of User Behavior

Coding Horror - Jeff Atwood - Fri, 07/18/2014 - 01:05

I've long believed that the design of your software has a profound impact on how users behave within your software. But there are two sides to this story:

  • Encouraging the "right" things by making those things intentionally easy to do.

  • Discouraging the "wrong" things by making those things intentionally difficult, complex, and awkward to do.

Whether the software is doing this intentionally, or completely accidentally, it's a fact of life: the path of least resistance is everyone's best friend. Learn to master this path, or others will master it for you.

For proof, consider Dan Ariely's new and amazing book, The (Honest) Truth About Dishonesty: How We Lie to Everyone – Especially Ourselves.

Indeed, let's be honest: we all lie, all the time. Not because we're bad people, mind you, but because we have to regularly lie to ourselves as a survival mechanism. You think we should be completely honest all the time? Yeah. Good luck with that.

But these healthy little white lies we learn to tell ourselves have a darker side. Have you ever heard this old adage?

One day, Peter locked himself out of his house. After a spell, the locksmith pulled up in his truck and picked the lock in about a minute.

“I was amazed at how quickly and easily this guy was able to open the door,” Peter said. The locksmith told him that locks are on doors only to keep honest people honest. One percent of people will always be honest and never steal. Another 1% will always be dishonest and always try to pick your lock and steal your television; locks won’t do much to protect you from the hardened thieves, who can get into your house if they really want to.

The purpose of locks, the locksmith said, is to protect you from the 98% of mostly honest people who might be tempted to try your door if it had no lock.

I had heard this expressed less optimistically before as

10% of people will never steal, 10% of people will always steal, and for everyone else … it depends.

The "it depends" part is crucial to understanding human nature, and that's what Ariely spends most of the book examining in various tests. If for most people, honesty depends, what exactly does it depend on? The experiments Ariely conducts prove again and again that most people will consistently and reliably cheat "just a little", to the extent that they can still consider themselves honest people. The gating factor isn't laws, penalties, or ethics. Surprisingly, that stuff has virtually no effect on behavior. What does, though, is whether they can personally still feel like they are honest people.

This is because they don't even consider it cheating – they're just taking a little extra, giving themselves a tiny break, enjoying a minor boost, because well, haven't they been working extra specially hard lately and earned it? Don't they of all people deserve something nice once in a while, and who would even miss this tiny amount? There's so much!

These little white lies are the path of least resistance. They are everywhere. If laws don't work, if ethics classes don't work, if severe penalties don't work, how do you encourage people to behave in a way that "feels" honest that is actually, you know, honest? Feelings are some pretty squishy stuff.

It's easier than you think.

My colleagues and I ran an experiment at the University of California, Los Angeles. We took a group of 450 participants, split them into two groups and set them loose on our usual matrix task. We asked half of them to recall the Ten Commandments and the other half to recall 10 books that they had read in high school.

Among the group who recalled the 10 books, we saw the typical widespread but moderate cheating. But in the group that was asked to recall the Ten Commandments, we observed no cheating whatsoever. We reran the experiment, reminding students of their schools' honor codes instead of the Ten Commandments, and we got the same result. We even reran the experiment on a group of self-declared atheists, asking them to swear on a Bible, and got the same no-cheating results yet again.

That's the good news: a simple reminder at the time of the temptation is usually all it takes for people to suddenly "remember" their honesty.

The bad news is Clippy was right.

In my experience, nobody reads manuals, nobody reads FAQs, and nobody reads tutorials. I am exaggerating a little here for effect, of course. Some A+ students will go out of their way to read these things. That's how they became A+ students, by naturally going the extra mile, and generally being the kind of users who teach themselves perfectly well without needing special resources to get there. When I say "nobody" I mean the vast overwhelming massive majority of people you would really, really want to read things like that. People who don't have the time or inclination to expend any effort at all other than the absolute minimum required, people who are most definitely not going to go the extra mile.

In other words, the whole world.

So how do you help people who, like us, just never seem to have the time to figure this stuff out becase they're, like, suuuuper busy and stuff?

You do it by showing them …

  • the minumum helpful reminder
  • at exactly the right time

This is what I've called the "Just In Time" theory of user behavior for years. Sure, FAQs and tutorials and help centers are great and all, but who has the time for that? We're all perpetual intermediates here, at best.

The closer you can get your software to practical, useful "Just In Time" reminders, the better you can help the users who are most in need. Not the A+ students who already read the FAQ, and studied the help center intently, but those users who never read anything. And now, thanks to Dan Ariely, I have the science to back this up. Even something as simple as putting your name on the top of a form to report auto insurance milage, rather than the bottom, resulted in a mysterious 10% increase in average miles reported. Having that little reminder right at the start that hey, your name is here on this form, inspired additional honesty. It works.

Did we use this technique on Stack Overflow and Stack Exchange? Indeed we did. Do I use this technique on Discourse? You bet, in even more places, because this is social discussion, not technical Q&A. We are rather big on civility, so we like to remind people when they post on Discourse they aren't talking to a computer or a robot, but a real person, a lot like you.

When's the natural time to remind someone of this? Not when they sign up, not when they're reading, but at the very moment they begin typing their first words in their first post. This is the moment of temptation when you might be super mega convinced that someone is Wrong on the Internet. So we put up a gentle little reminder Just In Time, right above where they are typing:

Then hopefully, as Dan Ariely showed us with honesty, this little reminder will tap into people's natural reserves of friendliness and civility, so cooler heads will prevail – and a few people are inspired to get along a little better than they did yesterday. Just because you're on the Internet doesn't mean you need to be yelling at folks 24/7.

We use this same technique a bunch of other places: if you are posting a lot but haven't set an avatar, if you are adding a new post to a particularly old conversation, if you are replying a bunch of times in the same topic, and so forth. Wherever we feel a gentle nudge might help, at the exact time the behavior is occurring.

It's important to understand that we use these reminders in Discourse not because we believe people are dumb; quite the contrary, we use them because we believe people are smart, civil, and interesting. Turns out everyone just needs to be reminded of that once in a while for it to continue to be true.

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Categories: Programming

Upgrade now to Calendar APIv3

Google Code Blog - Thu, 07/17/2014 - 19:30
Cross-posted from the Google Apps Developers Blog

Back in 2011, we launched Calendar APIv3, which offers developers several improvements over older versions of the API, including better support for recurring events and lightweight resource representation in JSON. At that same time, we also announced that the older versions of the API – v1 and v2 – would be entering a three-year deprecation period in order to give developers time to migrate to the new version. Those three years are coming to an end, and on November 17, the v1 and v2 endpoints will be shut down. If you haven’t already done so, you should migrate your application now to APIv3 so that it continues to work after that date (and to start taking advantage of all that the new API offers!).

For additional resources, check out our Migration and Getting started guides. And if you have questions or issues, please reach out to us on StackOverflow.com, using tag #google-calendar.

By Lucia Fedorova, Calendar API Team

Lucia Fedorova is a Tech Lead of the Google Calendar API team. The team focuses on providing a great experience to Google Calendar developers and enabling new and exciting integrations.

Posted by Louis Gray, Googler
Categories: Programming

Agile and the Definition of Quality

“Quality begins on the inside... then works its way out.” -- Bob Moawad

Quality is value to someone.

Quality is relative.

Quality does not exist in a non-human vacuum.

Who is the person behind a statement about quality?

Who’s requirements count the most?

What are people willing to pay or do to have their requirements met?

Quality can be elusive if you don’t know how to find it, or you don’t know where to look.  Worse, even when you know where to look, you need to know how to manage the diversity of conflicting views.

On a good note, Agile practices and an Agile approach can help you surface and tackle quality in a tractable and pragmatic way.

In the book Agile Impressions, by “the grandfather of Agile Programming”, Jerry Weinberg shares insights and lessons learned around the relativity of quality and how to make decisions about quality more explicit and transparent.

Example of Conflicting Ideas About Software Quality

Here are some conflicting ideas about what constitutes software quality, according to Weinberg:

“Zero defects is high quality.”
“Lots of features is high quality.”
Elegant coding is high quality.”
“High performance is high quality.”
”Low development cost is high quality.”
“Rapid development is high quality.”
“User-friendliness is high quality.”

More Quality for One Person, May Mean Less for Another

There are always trade-offs.  It can be a game of robbing Peter to pay Paul.

Via Agile Impressions:

“Recognizing the relativity of quality often resolves the semantic dilemma. This is a monumental contribution, but it still does not resolve the political dilemma:  More quality for one person may mean less quality for another.”

The Relativity of Quality

Quality is relative.

Via Agile Impressions:

“The reason for my dilemma lies in the relativity of quality. As the MiniCozy story crisply illustrates, what is adequate quality to one person may be inadequate quality to another.”

Quality Does Not Exist in a Non-Human Vacuum

So many

Via Agile Impressions:

“If you examine various definitions of quality, you will always find this relativity. You may have to examine with care, though, for the relativity is often hidden, or at best, implicit.

In short, quality does not exist in a non-human vacuum, but every statement about quality is a statement about some person(s).  That statement may be explicit or implicit. Most often, the “who” is implicit, and statements about quality sound like something Moses brought down from Mount Sinai on a stone tablet.  That’s why so many discussions of software quality are unproductive: It’s my stone tablet versus your Golden Calf.”

Ask, Who is the Person Behind that Statement About Quality?

The way to have more productive conversations about quality is to find out who is the person behind a specific statement about quality.

Via Agile Impressions:

“When we encompass the relativity of quality, we have a tool to make those discussions more fruitful.  Each time somebody asserts a definition of software quality, we simply ask, “Who is the person behind that statement about quality.”

Quality Is Value To Some Person

Whose requirements count the most?

Via Agile Impressions:

“The political/emotional dimension of quality is made evident by a somewhat different definition of quality.  The idea of ‘requirements’ is a bit too innocent to be useful in this early stage, because it says nothing about whose requirements count the most. A more workable definition would be this:

‘Quality is value to some person.’

By ‘value,’ I mean, ‘What are people willing to pay (do) to have their requirements met.’ Suppose, for instance, that Terra were not my niece, but the niece of the president of the MiniCozy Software Company.  Knowing MiniCozy’s president’s reputation for impulsive emotional action, the project manager might have defined “quality” of the word processor differently.  In that case, Terra’s opinion would have been given high weight in the decision about which faults to repair.”

The Definition of “Quality” is Always Political and Emotional

Quality is a human thing.

Via Agile Impressions:

“In short, the definition of ‘quality’ is always political and emotional, because it always involves a series of decisions about whose opinions count, and how much they count relative to one another. Of course, much of the time these political/emotional decisions– like all important political/emotional decisions–are hidden from public view. Most of us software people like to appear rational. That’s why very few people appreciate the impact of this definition of quality on the Agile approaches.”

Agile Teams Can Help Make Decisions About Quality More Explicit Transparent

Open processes and transparency can help arrive at a better quality bar.

Via Agile Impressions:

“What makes our task even more difficult is that most of the time these decisions are hidden even from the conscious minds of the persons who make them.  That’s why one of the most important actions of an Agile team is bringing such decisions into consciousness, if not always into public awareness. And that’s why development teams working with an open process (like Agile) are more likely to arrive at a more sensible definition of quality than one developer working alone. To me, I don’t consider Agile any team with even one secret component.”

The "Customer" Must Represent All Significant Decisions of Quality

The quality of your product will be gated by the quality of your representation.

Via Agile Impressions:

“Customer support is another emphasis in Agile processes, and this definition of quality guides the selection of the ‘customers.’ To put it succinctly, the ‘ customer’ must actively represent all of the significant definitions of ‘quality.’ Any missing component of quality may very likely lead to a product that’s deficient in that aspect of quality.”

If You Don’t Have Suitable Representation of Views on Quality, You’re Not Agile

It’s faster and far more efficient to ignore people and get your software done.  But it’s far less effective.  Your amplify your effectiveness for addressing quality by involving the right people, in the right way, at the right time.  That’s how you change your quality game.

Via Agile Impressions:

“As a consultant to supposedly Agile teams, I always examine whether or not they have active participation of a suitable representation of diverse views of their product’s quality. If they tell me, “We can be more agile if we don’t have to bother satisfying so many people, then they may indeed by agile, but they’re definitely not Agile.”

I’ve learned a lot about quality over the years.  Many of Jerry Weinberg’s observations and insights match what I’ve experienced across various projects, products, and efforts.   The most important thing I’ve learned is how much value is in the eye of the beholder and the stakeholder and that quality is something that you directly impact by having the right views involved throughout the process.

Quality is not something you can bolt on or something that you can patch.

While you can certainly improve things, so much of quality starts up front with vision and views of the end in mind.

You might even say that quality is a learning process of realizing the end in mind.

For me, quality is a process of vision + rapid learning loops to iterate my way through the jungle of conflicting and competing views and viewpoints, while brining people along the journey.

Categories: Architecture, Programming

Can I Be A Professional Mobile Developer? (iOS / Android)

Making the Complex Simple - John Sonmez - Thu, 07/17/2014 - 15:00

Yes. Yes, you can. At least I think so. In this video I talk about why.

The post Can I Be A Professional Mobile Developer? (iOS / Android) appeared first on Simple Programmer.

Categories: Programming

The New Roboto

Google Code Blog - Wed, 07/16/2014 - 18:00
By Christian Robertson, Android Visual Designer

Along with the Material Design guidelines we released a new version of the Roboto type family. A lot of things have changed as we tuned the font to work across more screen sizes and conditions, from watches to desktops, televisions to cars. It still keeps much of its character that made it successful for both phones and tablets, but almost every glyph has been tweaked and updated in some way.

We see Roboto as an evolving type family and plan to continue to change and update it as the system evolves. It used to be that a type family was designed once and then used without change for many years. Sometimes an updated version was released with a new name, sometimes by appending a "Neue" or "New". The old model for releasing metal typefaces doesn't make sense for an operating system that is constantly improving. As the system evolves over time, the type should evolve along with it.

The easiest way to identify the new version is to look for the R and K. They were some of the rowdier glyphs from version one and have been completely redrawn. Also check for the dots on the letter i or in the punctuation. We have rounded them out to make the types a little more friendly when you look at them closely. We also rounded out the sides of the upper case characters like O and C which makes the font feel less condensed even though it still has a high character count per line.

Some of the most significant changes are in the rhythm and spacing, especially for the caps. This isn't apparent as you look at individual glyphs, but makes for a better texture on the screen. Some of the more subtle fixes were to balance the weights between the caps and lowercase characters (the caps are slightly heavier in this version) and better correction for the distortions that occur in the obliqued italic characters.

Ultimately the purpose of a typeface is to serve the content and help people to understand it. We think that the new updates to Roboto along with the new Material Design guidelines will help it do more of just that.

Posted by Louis Gray, Googler
Categories: Programming

R: Apply a custom function across multiple lists

Mark Needham - Wed, 07/16/2014 - 06:04

In my continued playing around with R I wanted to map a custom function over two lists comparing each item with its corresponding items.

If we just want to use a built in function such as subtraction between two lists it’s quite easy to do:

> c(10,9,8,7,6,5,4,3,2,1) - c(5,4,3,4,3,2,2,1,2,1)
 [1] 5 5 5 3 3 3 2 2 0 0

I wanted to do a slight variation on that where instead of returning the difference I wanted to return a text value representing the difference e.g. ’5 or more’, ’3 to 5′ etc.

I spent a long time trying to figure out how to do that before finding an excellent blog post which describes all the different ‘apply’ functions available in R.

As far as I understand ‘apply’ is the equivalent of ‘map’ in Clojure or other functional languages.

In this case we want the mapply variant which we can use like so:

> mapply(function(x, y) { 
    if((x-y) >= 5) {
        "5 or more"
    } else if((x-y) >= 3) {
        "3 to 5"
    } else {
        "less than 5"
    }    
  }, c(10,9,8,7,6,5,4,3,2,1),c(5,4,3,4,3,2,2,1,2,1))
 [1] "5 or more"   "5 or more"   "5 or more"   "3 to 5"      "3 to 5"      "3 to 5"      "less than 5"
 [8] "less than 5" "less than 5" "less than 5"

We could then pull that out into a function if we wanted:

summarisedDifference <- function(one, two) {
  mapply(function(x, y) { 
    if((x-y) >= 5) {
      "5 or more"
    } else if((x-y) >= 3) {
      "3 to 5"
    } else {
      "less than 5"
    }    
  }, one, two)
}

which we could call like so:

> summarisedDifference(c(10,9,8,7,6,5,4,3,2,1),c(5,4,3,4,3,2,2,1,2,1))
 [1] "5 or more"   "5 or more"   "5 or more"   "3 to 5"      "3 to 5"      "3 to 5"      "less than 5"
 [8] "less than 5" "less than 5" "less than 5"

I also wanted to be able to compare a list of items to a single item which was much easier than I expected:

> summarisedDifference(c(10,9,8,7,6,5,4,3,2,1), 1)
 [1] "5 or more"   "5 or more"   "5 or more"   "5 or more"   "5 or more"   "3 to 5"      "3 to 5"     
 [8] "less than 5" "less than 5" "less than 5"

If we wanted to get a summary of the differences between the lists we could plug them into ddply like so:

> library(plyr)
> df = data.frame(x=c(10,9,8,7,6,5,4,3,2,1), y=c(5,4,3,4,3,2,2,1,2,1))
> ddply(df, .(difference=summarisedDifference(x,y)), summarise, count=length(x))
   difference count
1      3 to 5     3
2   5 or more     3
3 less than 5     4
Categories: Programming

Noto: A CJK Font That is Complete, Beautiful and Right for Your Language and Region

Google Code Blog - Tue, 07/15/2014 - 23:00
By Xiangye Xiao, Stuart Gill, and Jungshik Shin,
Google Text and Font Team, Internationalization Engineering


Chinese, Japanese and Korean (CJK) readers represent approximately one quarter of the world’s population. Google’s mission is to organize the world’s information and make it universally accessible to all users no matter what language they use. To that end, Google, in cooperation with our partner Adobe, has released a free, high-quality Pan-CJK font family: Noto Sans CJK. These fonts are intended to provide a richer and more beautiful reading experience to the East Asian community in many OSes and software applications.


Noto Sans CJK comprehensively covers Simplified Chinese, Traditional Chinese, Japanese, and Korean in a unified font family and yet conveys the expected aesthetic preferences of each language. Noto Sans CJK is a sans serif typeface designed as an intermediate style between the modern and traditional. It is intended to be a multi-purpose digital font for user interface designs, digital content, reading on laptops, mobile devices, and electronic books. Noto Sans CJK is provided in seven weights: Thin, Light, DemiLight, Regular, Medium, Bold, and Black.


Fully supporting CJK requires tens of thousands of characters—these languages share the majority of ideographic characters, but there are also characters that are unique to only one language or to a subset of the languages. One of the primary design goals of Noto Sans CJK is that each script should retain its own distinctive look, which follows regional conventions, while remaining harmonious with the others.

Chinese ideographic characters are not only used by Simplified and Traditional Chinese, where they are called hanzi, but also by Japanese (kanji) and Korean (hanja). Although all originated from ancient Chinese forms, in each region and language they evolved independently. As a result, the same character can vary in shape across the different languages. For example, the image below shows variants of the same character (骨 - bone) designed for Simplified Chinese, Traditional Chinese, Japanese, and Korean. Look at how the inner top part and inner bottom part are different. Noto Sans CJK is designed to take these variations into account. In addition to ideographic characters, Noto Sans CJK also supports Japanese kana and Korean Hangeul—both contemporary and archaic.


Google and Adobe partnered to develop this free high-quality Pan-CJK typeface. Google will release it as Noto Sans CJK as part of Google's Noto font family. Adobe will release it as Source Han Sans as a part of Adobe's Source family. Adobe holds the copyright to the typeface design, and the fonts are released under the Apache License, version 2.0 which makes them freely available to all without restriction.

About this partnership: Google contributed significant input into project direction, helped to define requirements, provided in-country testing resources and expertise, and provided funding that made this project possible. Adobe brought strong design and technical prowess to the table, along with proven in-country type design experience, massive coordination, and automation. In addition, three leading East Asian type foundries were also brought in to design and draw a bulk of the glyphs—Changzhou SinoType Technology, Iwata Corporation, and Sandoll Communication—due to the sheer size of the project and their local expertise.

Building Noto Sans CJK font is a major step towards our mission to make the reading experience beautiful for all users on all devices. Noto Sans CJK is the newest member of the Noto font family, which aims to support all languages in the world. The entire Noto font family, including Noto Sans CJK, is free and open. Visit the Noto homepage to download Noto Sans CJK and other Noto fonts.

Xiangye Xiao is a Product Manager at Google Inc. where she works on fonts and text input.
Stuart Gill is the Tech Lead and Manager of Google’s Text and Font team.

Jungshik Shin is the Noto visionary and is a Software Engineer in Google’s Internationalization Engineering team working on Text and Fonts as well as on Chrome.


Posted by Louis Gray, Googler
Categories: Programming

Learn to Think Like an Android Developer

Android Developers Blog - Tue, 07/15/2014 - 19:57

By Reto Meier, Head of Scalable Developer Advocacy

Today I’m proud to announce the latest resource for learning to develop Android apps: Developing Android Apps: Android Fundamentals.

Android Fundamentals is an online training course featuring Google Developer Advocates Reto Meier, Dan Galpin, and Katherine Kuan, working with the team at Udacity that’s advanced and technical enough for experienced developers who are new to Android — maybe even new to mobile — but not new to programming.

The course offers step-by-step training in which you’ll build an Android app, and learn best practices of mobile development in general and Android development in particular.

The full course materials — all the videos, quizzes, and forums — are available for free for all students by selecting “View Courseware”. Personalized ongoing feedback and guidance from Coaches is also available to anyone who chooses to enroll in Udacity’s guided program.

This guided course, along with UX Design for Mobile Developers and Mobile Web Development, complement our existing material—including documentation, samples, and videos — to offer a solid grounding in developing great experiences for people using mobile devices. Check out the trailer below for an overview of what's in the course.

Mobile devices are the platform that will bring the next five billion people online. With Android expanding rapidly into emerging markets, and growing beyond phones and tablets into wearables, auto, and TV, learning the fundamentals behind Android development represents an opportunity to affect and improve the lives of billions of people.

We look forward to seeing what the next wave of Android developers build, and we’ll keep exploring new ways to help you become better developers.



Join the discussion on
+Android Developers


Categories: Programming

Whitepaper on Getting QA and Developers To Work Together and Upcoming Webinar

Making the Complex Simple - John Sonmez - Tue, 07/15/2014 - 16:43

Just wanted to do a short post to talk about a whitepaper I wrote for one of the companies that has been a big supporter of this blog, Zephyr, and also invite you to check out a webinar I’ll be doing next week on “How trying to learn too much may actually be hurting you–and […]

The post Whitepaper on Getting QA and Developers To Work Together and Upcoming Webinar appeared first on Simple Programmer.

Categories: Programming

The 4 Levels of Freedom For Software Developers

Making the Complex Simple - John Sonmez - Mon, 07/14/2014 - 16:00

For quite some time now I’ve been putting together, in my mind, what I think are the four distinct levels that software developers can go through in trying to gain their “freedom.” For most of my software development career, when I worked for a company, as an employee, I had the dream of someday being […]

The post The 4 Levels of Freedom For Software Developers appeared first on Simple Programmer.

Categories: Programming