15 January 2015

How Google Analytics helps you make better decisions for your apps

Posted by Russell Ketchum, Lead Product Manager, Google Analytics for Mobile Apps

Knowing how your customers use your app is the foundation to keeping them happy and engaged. It’s important to track downloads and user ratings, but the key to building a successful business is using data to dive deeper into understanding the full acquisition funnel and what makes users stick around.

Google Analytics is the easiest way to understand more about what your users are doing inside your app on Google Play, while also simultaneously tracking your users across the web and other mobile platforms. To show how Google Analytics can help, we've created a new "Analyze" section on the Android Developers website for you to check out. We provide guidance on how to design a measurement plan and implement effective in-app analytics – and take advantage of features only available between Google Play and Google Analytics.

The Google Play Referral Flow in Analytics

Google Analytics for mobile apps provides a comprehensive view into your app’s full user lifecycle, including user acquisition, composition, in app behavior, and key conversions. Our Analytics Academy course on mobile app analytics is also a great resource to learn the fundamentals.

Eltsoft LLC, a foreign language learning and education app developer for Android, recognized early on how impactful Google Analytics would have on the company's ability to quickly improve on its apps and meet user needs.

Analytics has really helped us to track the effectiveness of the changes to our app. I would say six months ago, that our success was a mystery. The data said we were doing well, but the whys were not clear. Therefore, we couldn’t replicate or push forward. But today, we understand what’s happening and can project our future success. We have not only the data, but can control certain variables allowing us to understand that data. - Jason Byrne, Eltsoft LLC

Here are some powerful tips to make the most of Google Analytics:

  1. Understand the full acquisition funnel
  2. Uniquely integrated with the Google Play Developer Console, Google Analytics gives you a comprehensive view of the Google Play Referral Flow. By linking Analytics to the Developer Console, you can track useful data on how users move through the acquisition flow from your marketing efforts to the Google Play store listing to the action of launching the app. If you find that a significant number of users browse your app in Google Play, but don’t install it, for example, you can then focus your efforts on improving your store listing.
  3. Unlock powerful insights on in-app purchases
  4. Monitoring in-app purchases in the Google Play Developer Console will show you the total revenue your app is generating, but it does not give you the full picture about your paying users. By instrumenting your app with the Google Analytics ecommerce tracking, you’ll get a fuller understanding of what paying users do inside your app. For example, you can find out which acquisition channels deliver users who stay engaged and go on to become the highest value users.
  5. Identify roadblocks and common paths with the Behavior Flow
  6. Understanding how users move through your app is best done with in-app analytics. With Google Analytics, you can easily spot if a significant percentage of users leave your app during a specific section. For example, if you see significant drop off on a certain level of your game, you may want to make that level easier, so that more users complete the level and progress through the game. Similarly, if you find users who complete a tutorial stay engaged with your app, you might put the tutorial front and center for first-time users.
  7. Segment your audience to find valuable insights
  8. Aggregated data can help you answer questions about overall trends in your app. If you want to unlock deeper insights about what drives your users’ behavior, you can slice and dice your data using segmentation, such as demographics, behavior, or install date. If something changes in one of your key metrics, segmentation can help you get to the root of the issue -- for example, was a recent app update unpopular with users from one geographic area, or were users with a certain device or carrier affected by a bug?
  9. Use custom data to measure what matters for your business
  10. Simply activating the Google Analytics library gives you many out-of-the-box metrics without additional work, such as daily and monthly active users, session duration, breakdowns by country, and many more variables. However, it’s likely that your app has many user actions or data types that are unique to it, which are critical to building an engaged user base. Google Analytics provides events, custom dimensions, and custom metrics so you can craft a measurement strategy that fits your app and business.
  11. No more one-size-fits-all ad strategy
  12. If you’re a developer using AdMob to monetize your app, you can now see all of your Analytics data in the AdMob dashboard. Running a successful app business is all about reaching the right user with the right ad or product at the right time. If you create specific user segments in Google Analytics, you can target each segment with different ad products. For example, try targeting past purchasers with in-app purchase ads, while monetizing users who don’t purchase through targeted advertising.

By measuring your app performance on a granular level, you will be able to make better decisions for your business. Successful developers build their measurement plan at the same time as building their app in order to set goals and track progress against key success metrics, but it’s never too late to start.

Choose the implementation that works best for your app to get started with Google Analytics today and find out more about what you can do in the new “Analyze” section of developers.android.com.

Join the discussion on

+Android Developers

13 January 2015

Efficient Game Textures with Hardware Compression

Posted by Shanee Nishry, Developer Advocate

As you may know, high resolution textures contribute to better graphics and a more impressive game experience. Adaptive Scalable Texture Compression (ASTC) helps solve many of the challenges involved including reducing memory footprint and loading time and even increase performance and battery life.

If you have a lot of textures, you are probably already compressing them. Unfortunately, not all compression algorithms are made equal. PNG, JPG and other common formats are not GPU friendly. Some of the highest-quality algorithms today are proprietary and limited to certain GPUs. Until recently, the only broadly supported GPU accelerated formats were relatively primitive and produced poor results.

With the introduction of ASTC, a new compression technique invented by ARM and standardized by the Khronos group, we expect to see dramatic changes for the better. ASTC promises to be both high quality and broadly supported by future Android devices. But until devices with ASTC support become widely available, it’s important to understand the variety of legacy formats that exist today.

We will examine preferable compression formats which are supported on the GPU to help you reduce .apk size and loading times of your game.

Texture Compression

Popular compressed formats include PNG and JPG, which can’t be decoded directly by the GPU. As a consequence, they need to be decompressed before copying them to the GPU memory. Decompressing the textures takes time and leads to increased loading times.

A better option is to use hardware accelerated formats. These formats are lossy but have the advantage of being designed for the GPU.

This means they do not need to be decompressed before being copied and result in decreased loading times for the player and may even lead to increased performance due to hardware optimizations.

Hardware Accelerated Formats

Hardware accelerated formats have many benefits. As mentioned before, they help improve loading times and the runtime memory footprint.

Additionally, these formats help improve performance, battery life and reduce heating of the device, requiring less bandwidth while also consuming less energy.

There are two categories of hardware accelerated formats, standard and proprietary. This table shows the standard formats:

ETC1 Supported on all Android devices with OpenGL ES 2.0 and above. Does not support alpha channel.
ETC2 Requires OpenGL ES 3.0 and above.
ASTC Higher quality than ETC1 and ETC2. Supported with the Android Extension Pack.

As you can see, with higher OpenGL support you gain access to better formats. There are proprietary formats to replace ETC1, delivering higher quality and alpha channel support. These are shown in the following table:

ATC Available with Adreno GPU.
PVRTC Available with a PowerVR GPU.
DXT1 S3 DXT1 texture compression. Supported on devices running Nvidia Tegra platform.
S3TC S3 texture compression, nonspecific to DXT variant. Supported on devices running Nvidia Tegra platform.

That’s a lot of formats, revealing a different problem. How do you choose which format to use?

To best support all devices you need to create multiple apks using different texture formats. The Google Play developer console allows you to add multiple apks and will deliver the right one to the user based on their device. For more information check this page.

When a device only supports OpenGL ES 2.0 it is recommended to use a proprietary format to get the best results possible, this means making an apk for each hardware.

On devices with access to OpenGL ES 3.0 you can use ETC2. The GL_COMPRESSED_RGBA8_ETC2_EAC format is an improved version of ETC1 with added alpha support.

The best case is when the device supports the Android Extension Pack. Then you should use the ASTC format which has better quality and is more efficient than the other formats.

Adaptive Scalable Texture Compression (ASTC)

The Android Extension Pack has ASTC as a standard format, removing the need to have different formats for different devices.

In addition to being supported on modern hardware, ASTC also offers improved quality over other GPU formats by having full alpha support and better quality preservation.

ASTC is a block based texture compression algorithm developed by ARM. It offers multiple block footprints and bitrate options to lower the size of the final texture. The higher the block footprint, the smaller the final file but possibly more quality loss.

Note that some images compress better than others. Images with similar neighboring pixels tend to have better quality compared to images with vastly different neighboring pixels.

Let’s examine a texture to better understand ASTC:

This bitmap is 1.1MB uncompressed and 299KB when compressed as PNG.

Compressing the Android jellybean jar texture into ASTC through the Mali GPU Texture Compression Tool yields the following results.

Block Footprint 4x4 6x6 8x8
Memory 262KB 119KB 70KB
Image Output
Difference Map
5x Enhanced Difference Map

As you can see, the highest quality (4x4) bitrate for ASTC already gains over PNG in memory size. Unlike PNG, this gain stays even after copying the image to the GPU.

The tradeoff comes in the detail, so it is important to carefully examine textures when compressing them to see how much compression is acceptable.

Conclusion

Using hardware accelerated textures in your games will help you reduce the size of your .apk, runtime memory use as well as loading times.

Improve performance on a wider range of devices by uploading multiple apks with different GPU texture formats and declaring the texture type in the AndroidManifest.xml.

If you are aiming for high end devices, make sure to use ASTC which is included in the Android Extension Pack.

19 December 2014

Build Mobile App Services with Google Cloud Tools for Android Studio v1.0

Posted by Chris Sells, Product Manager, Cloud Tools for Android Studio

Cloud Tools for Android Studio allows you to simultaneously build the service- and client-side of your mobile app. Earlier this month, we announced the release of Android Studio 1.0 that showed just how much raw functionality there is available for Android app developers. However, the client isn’t the whole picture, as most mobile apps also need one or more web services. It was for this reason that the Cloud Tools for Android Studio were created.

Cloud Tools put the power of Google App Engine in the same IDE alongside of your mobile client, giving you all the same Java language tools for both sides of your app, as well as making it far easier for you to keep them in sync as each of them changes.

Getting Started

To get started with Cloud Tools for Android Studio, add a New Module to your Android Studio project, choose Google Cloud Module and you’ll have three choices:

You can add three Google Cloud module types to your Android Studio project

The Java Servlet Module gives you a plain servlet class for you to implement as you see fit. If you’d like help building your REST endpoints with declarative routing and HTTP verbs and automatic Java object serialization to and from JSON, then you’ll want the Java Endpoints Module. If you want the power of endpoints, along with the ability to send notifications from your server to your clients, then choose Backend with Google Cloud Messaging.

Once you’re done, you’ll have your service code right next to your client code:

You can build your mobile app’s client and service code together in a single project

Not only does this make it very convenient to build and test your entire end-to-end, but we also dropped a little extra something into your app’s build.gradle file:

The android-endpoints configuration build step in your build.gradle file creates a client-side library for your server-side endpoint

The updated Gradle file will now create a library for use in your app’s client code that changes when your service API changes. This library lets you call into your service from your client and provides full code completion as you do:

The client-side endpoint library provides code completion and documentation

Instead of writing the code to create HTTP requests by hand, you can make calls via the library in a typesafe manner and the marshalling from JSON to Java will be handled for you, just like on the server-side (but in reverse, of course).

Endpoints Error Detection

Meanwhile, back on the server-side, as you make changes to your endpoints, we’re watching to make sure that they’re in good working order even before you compile by checking the attributes as you type:

Cloud Tools will detect errors in your endpoint attributes

Here, Cloud Tools have found a duplicate name in the ApiMethod attribute, which is easy to do if you’re creating a new method from an existing method.

Creating an Endpoint from an Objectify Entity

If, as part of your endpoint implementation, you decide to take advantage of the popular Objectify library, you’ll find that Cloud Tools provides special support for you. When you right-click (or control-click on the Mac) on a file containing an Objectify entity class, you’ll get the Generate Cloud Endpoint from Java class option:

The generate Cloud Endpoint from Java class option will create a CRUD endpoint for you

If you’re running this option on a Java class that isn’t built with Objectify, then you’re going to get an endpoint with empty methods for get and insert operations that you can implement as appropriate. However, if you do this with an Objectify entity, you’ll get a fully implemented endpoint:

Cloud Tools has built-in support for generating Objectify-based cloud endpoint implementations

Using your Cloud Endpoint

As an Android developer, you’re used to deploying your client first in the emulator and then into a local device. Likewise, with the service, you’ll want to test first to your local machine and then, when you’re ready, deploy into a Google App Engine project. You can run your service app locally by simply choosing it from the Configurations menu dropdown on the toolbar and pressing the Run button:

The Configurations menu in the toolbar lets you launch your service for testing

This will build and execute your service on http://localhost:8080/ (by default) so that you can test against it with your Android app running in the emulator. Once you’re ready to deploy to Google Cloud Platform, you can do so by selecting the Deploy Module to App Engine option from the Build menu, where you’ll be able to choose the source module you want to deploy, log into your Google account and pick the target project to which you’d like to deploy:

The Deploy to App Engine dialog will use your Google credentials to enumerate your projects for you

Cloud Tools beta required some extra copying and pasting to get the Google login to work, but all of that’s gone now in this release.

What’s Next?

We’re excited to get this release into your hands, so if you’ve haven’t downloaded it yet, then go download Android Studio 1.0 right now! To take advantage of Cloud Tools for Android Studio, you’ll want to sign up for a free Google Cloud Platform trial. Nothing is stopping you from building great Android apps from front to back. If you’ve got suggestions, drop us a line so that we can keep improving. We’re just getting started putting Google Cloud Platform tools in your hands. We can’t wait to see what you’ll build.

Google Play game services ends year with a bang!

Posted by Benjamin Frenkel, Product Manager, Play Games

In an effort to supercharge our Google Play games services (GPGS) developer tools, we’re introducing the Game services Publishing API, a revamped Unity Plugin, additional enhancements to the C++ SDK, and improved Leaderboard Tamper Protection.

Let’s dig into what’s new for developers:

Publishing API to automate game services configuration

At Google I/O this past June, the pubsite team launched the Google Play Developer Publishing APIs to automate the configuration and publishing of applications to the Play store. Game developers can now also use the Google Play game services Publishing API to automate the configuration and publishing of game services resources, starting with achievements and leaderboards.

For example, if you plan on publishing your game in multiple languages, the game services Publishing API will enable you to pull translation data from spreadsheets, CSVs, or a Content Management System (CMS) and automatically apply those translations to your achievements.

Early adopter Square Enix believes the game services Publishing API will be an indispensable tool to manage global game rollouts:


Achievements are the most used feature in Google Play game services for us. As our games support more languages, achievement management has become increasingly difficult. With the game services Publishing API, we can automate this process, which is really helpful. The game services Publishing API also comes with great samples that we were able to easily customize for our needs

Keisuke Hata, Manager / Technical Director, SQUARE ENIX Co., Ltd.





To get started today, take a look at the developer documentation here.

Updated Unity plugin and Cross-platform C++ SDK

  • Unity plugin Saved Games support: You can now take advantage of the Saved Games feature directly from the Unity plugin, with more storage and greater discoverability through the Play Games app
  • New Unity plugin architecture: We’ve rewritten the plugin on top of our cross-platform C++ SDK to speed up feature development across SDKs and increase our responsiveness to your feedback
  • Improved Unity generated Xcode project setup: You now have a much more robust way to generate Xcode projects integrated with Google Play Game Services in Unity
  • Updated and improved Unity samples: We’ve updated our sample codes to make it easier for first time developers to integrate Google Play games services
  • C++ SDK support for iPhone 6 Plus: You can now take advantage of the out-of-box games services UI (e.g., for leaderboards and achievements) for larger form factor devices, such as the iPhone 6 Plus

We also include some important bug fixes and stability improvements. Check out the release notes for the Unity Plugin and the getting started page for the C++ SDK for more details.

Leaderboard Tamper Protection

Turn on Leaderboard Tamper Protection to automatically hide suspected tampered scores from your leaderboards. To enable tamper protection on an existing leaderboard, go to your leaderboard in the Play developer console and flip the “Leaderboard tamper protection” toggle to on. Tamper protection will be on by default for new leaderboards.Learn more.

To learn more about cleaning up previously submitted suspicious scores refer to the Google Play game services Management APIs documentation or get the web demo console for the Management API directly from github here.

In addition, if you prefer command-line tools, you can use the python-based option here.

18 December 2014

Making a performant watch face

Posted by Hoi Lam, Developer Advocate, Android Wear

What’s a better holiday gift than great performance? You’ve got a great watch face idea -- now, you want to make sure the face you’re presenting to the world is one of care and attention to detail.

At the core of the watch face's process is an onDraw method for canvas operations. This allows maximum flexibility for your design, but also comes with a few performance caveats. In this blog post, we will mainly focus on performance using the real life journey of how we optimised the Santa Tracker watch face, more than doubling the number of fps (from 18 fps to 42 fps) and making the animation sub-pixel smooth.

Starting point - 18 fps

Our Santa watch face contains a number of overlapping bitmaps that are used to achieve our final image. Here's a list of them from bottom to top:

  1. Background (static)
  2. Clouds which move to the middle
  3. Tick marks (static)
  4. Santa figure and sledge (static)
  5. Santa’s hands - hours and minutes
  6. Santa’s head (static)

The journey begins with these images...

Large images kill performance (+14 fps)

Image size is critical to performance in a Wear application, especially if the images will be scaled and rotated. Wasted pixel space (like Santa’s arm here) is a common asset mistake:

Before: 584 x 584 = 341,056 pixelsAfter: 48*226 = 10,848 (97% reduction)

It's tempting to use bitmaps from the original mock up that have the exact location of watch arms and components in absolute space. Sadly, this creates problems, like in Santa's arm here. While the arm is in the correct position, even transparent pixels increase the size of the image, which can cause performance problems due to memory fetch. You'll want to work with your design team to extract padding and rotational information from the images, and rely on the system to apply the transformations on our behalf.

Since the original image covers the entire screen, even though the bitmap is mostly transparent, the system still needs to check every pixel to see if they have been impacted. Cutting down the area results in significant gains in performance. After correcting both of the arms, the Santa watch face frame rate increased by 10 fps to 28 fps (fps up 56%). We saved another 4 fps (fps up 22%) by cropping Santa’s face and figure layer. 14 fps gained, not bad!

Combine Bitmaps (+7 fps)

Although it would be ideal to have the watch tick marks on top of our clouds, it actually does not make much difference visually as the clouds themselves are transparent. Therefore there is an opportunity to combine the background with the ticks.

+

When we combined these two views together, it meant that the watch needed to spend less time doing alpha blending operations between them, saving precious CPU time. So, consider collapsing alpha blended resources wherever we can in order to increase performance. By combining two full screen bitmaps, we were able to gain another 7 fps (fps up 39%).

Anti-alias vs FilterBitmap flags - what should you use? (+2 fps)

Android Wear watches come in all shapes and sizes. As a result, it is sometimes necessary to resize a bitmap before drawing on the screen. However, it is not always clear what options developers should select to make sure that the bitmap comes out smoothly. With canvas.drawBitmap, developers need to feed in a Paint object. There are two important options to set - they are anti-alias and FilterBitmap. Here’s our advice:

  • Anti-alias does not do anything for bitmaps with transparent edges. We often switch on the anti-alias option by default as developers when we are creating a Paint object. However, this option only really makes sense for vector objects. For bitmaps, this is used to blend the rectangular edges if it is rotated or skewed and it has no impact if the edge pixels are transparent (as we would imagine most watch face arms would be). The hand on the left below has anti-alias switched on, the one on the right has it switched off. So turn off anti-aliasing for bitmaps to gain performance back. For our watch face, we gained another 2 fps (fps up 11%) by switching this option off.
  • Switch on FilterBitmap for all bitmap objects which are on top of other objects - this option smooths the edges when drawBitmap is called. This should not be confused with the filter option on Bitmap.createScaledBitmap for resizing bitmaps. We need both to be turned on. The bitmaps below are the magnified view of Santa’s hand. The one on the left has FilterBitmap switched off and the one on the right has FilterBitmap switched on.

Eliminate expensive calls in the onDraw loop (+3 fps)

onDraw is the most critical function call in watch faces. It's called for every drawable frame, and the actual painting process cannot move forward until it's finished. As such, our onDraw method should be as light and as performant as possible. Here's some common problems that developers run into that can be avoided:

  1. Do move heavy and common code to a precompute function - e.g. if we commonly grab R.array.cloudDegrees, try doing that in onCreate, and just referencing it in the onDraw loop.
  2. Don’t repeat the same image transform in onDraw - it’s common to resize bitmaps at runtime to fit the screen size but this is not available in onCreate. To avoid resizing the bitmap over and over again in onDraw, override onSurfaceChanged where width and height information are available and resize images there.
  3. Don't allocate objects in onDraw - this leads to high memory churn which will force garbage collection events to kick off, killing frame rates.
  4. Do analyze the CPU performance by using a tool such as the Android Device Monitor. It’s important that the onDraw execution time is short and occurs in a regular period.

Following these simple rules will improve rendering performance drastically.

In the first version, the Santa onDraw routine has a rogue line:

int[] cloudDegrees = 
    getResources().getIntArray(R.array.cloudDegrees);

This loads the int array on every call from resources which is expensive. By eliminating this, we gained another 3 fps (fps up 17%).

Sub-pixel smooth animation (-2 fps)

For those keeping count, we should be 44 fps, so why is the end product 42 fps? The reason is a limitation with canvas.drawBitmap. Although this command takes left and top positioning settings as a float, the API actually only deals with integers if it is purely translational for backwards compatibility reasons. As a result, the cloud can only move in increments of a whole pixel resulting in janky animations. In order to be sub-pixel smooth, we actually need to draw and then rotate rather than having pre-rotate clouds which moves towards Santa. This additional rotation costs us 2 fps. However, the effect is worthwhile as the animation is now sub-pixel smooth.

Before - fast but janky and wobbly

for (int i = 0; i < mCloudBitmaps.length; i++) {
    float r = centerX - (timeElapsed / mCloudSpeeds[i]) % centerX;
    float x = centerX + 
        -1 * (r * (float) Math.cos(Math.toRadians(cloudDegrees[i] + 90)));
    float y = centerY - 
        r * (float) Math.sin(Math.toRadians(cloudDegrees[i] + 90));
    mCloudFilterPaints[i].setAlpha((int) (r/centerX * 255));
    Bitmap cloud = mCloudBitmaps[i];
    canvas.drawBitmap(cloud,
        x - cloud.getWidth() / 2,
        y - cloud.getHeight() / 2,
        mCloudFilterPaints[i]);
}

After - slightly slower but sub-pixel smooth

for (int i = 0; i < mCloudBitmaps.length; i++) {
    canvas.save();
    canvas.rotate(mCloudDegrees[i], centerX, centerY);
    float r = centerX - (timeElapsed / (mCloudSpeeds[i])) % centerX;
    mCloudFilterPaints[i].setAlpha((int) (r / centerX * 255));
    canvas.drawBitmap(mCloudBitmaps[i], centerX, centerY - r,
        mCloudFilterPaints[i]);
    canvas.restore();
}

Before: Integer translation values create janky, wobbly animation. After: smooth sailing!

Quality on every wrist

The watch face is the most prominent UI element in Android Wear. As craftspeople, it is our responsibility to make it shine. Let’s put quality on every wrist!

11 December 2014

New Code Samples for Lollipop

Posted by Trevor Johns, Developer Programs Engineer

With the launch of Android 5.0 Lollipop, we’ve added more than 20 new code samples demonstrating how to implement some of the great new features of this release. To access the code samples, you can easily import them in Android Studio 1.0 using the new Samples Wizard.

Go to File > Import Sample in order to browse the available samples, which include a description and preview for each. Once you’ve made your selection, select “Next” and a new project will be automatically created for you. Run the project on an emulator or device, and feel free to experiment with the code.

Samples Wizard in Android Studio 1.0
Newly imported sample project in Android Studio

Alternatively, you can browse through them via the Samples browser on the developer site. Each sample has an Overview description, Project page to browse app file structure, and Download link for obtaining a ZIP file of the sample. As a third option, code samples can also be accessed in the SDK Manager by downloading the SDK samples for Android 5.0 (API 21) and importing them as existing projects into your IDE.


Sample demonstrating transition animations

Material Design

When adopting material design, you can refer to our collection of sample code highlighting material elements:

For additional help, please refer to our design checklist, list of key APIs and widgets, and documentation guide.

To view some of these material design elements in action, check out the Google I/O app source code.

Platform

Lollipop brings the most extensive update to the Android platform yet. The Overview screen allows an app to surface multiple tasks as concurrent documents. You can include enhanced notifications with this sample code, which shows you how to use the lockscreen and heads-up notification APIs.

We also introduced a new Camera API to provide developers more advanced image capture and processing capabilities. These samples detail how to use the camera preview and take photos, how to record video, and implement a real-time high-dynamic range camera viewfinder.

Elsewhere, Project Volta encourages developers to make their apps more battery-efficient with new APIs and tools. The JobScheduler sample demonstrates how you can schedule background tasks to be completed later or under specific conditions.

For those interested in the enterprise device administration use case, there are sample apps on setting app restrictions and creating a managed profile.

Android Wear

For Android Wear, we have a speed tracker sample to show how to take advantage of GPS support on wearables. You can browse the rest of the Android Wear samples too, and here are some highlights that demonstrate the unique capabilities of wearables, such as data synchronization, notifications, and supporting round displays:

Android TV

Extend your app for Android TV using the Leanback library described in this training guide and sample.

To try out a game that is specifically optimized for Android TV, download Pie Noon from Google Play. It’s an open-source game developed in-house at Google that supports multiple players using Bluetooth controllers or touch controls on mobile devices.

Android Auto

For the use cases highlighted in the Introduction to Android Auto DevByte, we have two code samples. The Media Browser sample (DevByte) demonstrates how easy it is to make an audio app compatible with Android Auto by using the new Lollipop media APIs, while the Messaging sample (DevByte) demonstrates how to implement notifications that support replies using speech recognition.

Google Play services

Since we’ve discussed sample resources for the Android platform and form factors, we also want to mention that there are existing samples for Google Play services. With Google Play services, your app can take advantage of the latest Google-powered APIs such as Maps, Google Fit, Google Cast, and more. Access samples in the Google Play services SDK or visit the individual pages for each API on the developer site. For game developers, you can reference the Google Play Games services samples for how to add achievements, leaderboards, and multiplayer support to your game.

Check out a sample today to help you with your development!

Hello World, meet our new experimental toolchain, Jack and Jill

Posted by Paul Rashidi, Developer Programs Engineer

We've been working on a new toolchain for Android that’s designed to improve build times and simplify development by reducing dependencies on other tools. Today, we’re introducing you to Jack (Java Android Compiler Kit) and Jill (Jack Intermediate Library Linker), the two tools at the core of the new toolchain.

We are making an early, experimental version of Jack and Jill available for testing with non-production versions of your apps. This post describes how the toolchain works, how to configure it, and how to let us know of your feature requests and any bugs you find.

So how does it work?

When the new tool chain is enabled, Jill will translate any libraries you are referencing to a new Jack library file (.jack). This prepares them to be quickly merged with other .jack files. The Android Gradle plugin and Jack collect any .jack library files, along with your source code, and compiles them into a set of dex files. During the process, Jack also handles any requested code minification. The output is then assembled into an APK file as normal. We also include support for multiple dex files, if you have enabled that support.

How do I use it?

Jack and Jill are already available in the 21.1.1+ Build Tools for Android Studio. Complementary Gradle support is also currently available in the Android 1.0.0+ Gradle plugin. To get started, all you need to do is make sure you're using these versions of the tooling and then add a single line in your build.gradle file. Perform a build of your application to receive a newly built APK.

android {
    ...
    buildToolsRevision '21.1.1'
    defaultConfig {
      // Enable the experimental Jack build tools.
      useJack = true
    }
    ...
}
If you want to build your app with both toolchains, Product Flavors are a great way to do this. Your build.gradle file might look something like the snippet below.
android {
    ...
    productFlavors {
        dev {
            ...
        }
        experimental {
            useJack = true
        }
        prod {
            ...
        }
    }
    ...
}

How do I configure my build?

We are making the transition to Jack as smooth as possible by supporting minification (shrinking and/or obfuscation), as well as repackaging (i.e. similar to tools like jarjar), while using the same input files as you are used to. Minification is available in the Gradle plugin immediately and repackaging will follow. You should continue to use the "minifyEnabled true" directive to reduce the size of your app among all other optimizations you would normally use. There are more details on our reference page (linked below) regarding the level of support for each type of optimization. We encourage you to provide feedback there if your current configuration isn't supported.

Give us your feedback

We are attempting to make the toolchain as easy to test out as possible and we're looking for your help to fine tune it. Use the reference page to find known issues, file feature requests, and report bugs. Happy building!