Memory management in NativeScript for Android

Note: This post will be a bit different from the previous ones. It’s intended to provide brief history as to why current NativeScript for Android implementation is designed this way. So, this post will be most useful for my Telerik ex-colleagues. Think of it as kind of historic documentation. Also, it is a chance to have a peek inside a developer’s mind 😉

I already gave you a hint about my current affairs. Since February I took the opportunity to pursue new ventures in a new company. The fact that my new office is the very next building to Telerik HQ gives me an opportunity to keep close connections with my former colleagues. At one such coffee break I was asked about the current memory management implementation. As I am no longer with Telerik, my former colleagues miss some important history that explains why this feature is implemented this way. I tried to explain briefly that particular technical issue in a previous post, however I couldn’t go much in depth because NativeScript was not announced yet. So, here I’ll try to provide more details.

Note: Keep in mind that this post is about NativeScript for Android platform, so I will focus only on that platform.

On the very first day of the project, we decided that we should explore what can be done with JavaScript-to-Java bidirectional marshalling. So, we set up a simple goal: make an app with a single button that increments a counter. Let’s see what Android docs says about button widget.

 public class MyActivity extends Activity {
     protected void onCreate(Bundle savedInstanceState) {


         final Button button = findViewById(;
         button.setOnClickListener(new View.OnClickListener() {
             public void onClick(View v) {
                 // Code here executes on main thread after user presses button

After so many years, this is the first code fragment you see on the site. And it should be so. This code fragment captures the very essence of what button widget is and how it is used. We wanted to provide JavaScript syntax which feels familiar to Java developers. So, we ended up with the following syntax:

var button = new android.widget.Button(context);
button.setOnClickListener(new android.view.View.OnClickListener({
   onClick: function() {
      // do some work

This example is shown countless times in NativeScript docs and various presentation slides/materials. It is part of our first and main test/demo app.

Motivation: we wanted to provide JavaScript syntax which is familiar to existing Android developers.

This decision brings an important implication, namely the usage of JavaScript closures. To understand why closures are important for the implementation, we could take a look at the following simple, but complete, Java example.

package com.example;

import android.os.Bundle;
import android.view.View;
import android.widget.Button;
import android.widget.LinearLayout;
import android.widget.TextView;

public class MyActivity extends Activity {
    private int count = 0;

    protected void onCreate(Bundle savedInstanceState) {

        LinearLayout layout = new LinearLayout(this);

        final TextView txt = new TextView(this);

        Button btn = new Button(this);
        btn.setOnClickListener(new View.OnClickListener() {
            public void onClick(View view) {
                txt.setText("Count:" + (++count));


Behind the scene, the Java compiler will generate anonymous class that we can decompile and inspect closely. For the purpose of this post I am going to use fernflower decompiler. Here is the output for MyActivity$1 class.

package com.example;

import android.view.View;
import android.view.View.OnClickListener;
import android.widget.TextView;

class MyActivity$1 implements OnClickListener {
   // $FF: synthetic field
   final TextView val$txt;
   // $FF: synthetic field
   final MyActivity this$0;

   MyActivity$1(MyActivity this$0, TextView var2) {
      this.this$0 = this$0;
      this.val$txt = var2;

   public void onClick(View view) {
      this.val$txt.setText("Count:" + MyActivity.access$004(this.this$0));

We can see the Java compiler generates code that:
1) captures the variable txt
2) deals with ++count expression

This means that the click handler object holds references to the objects it accesses in its closure. We can call this class stateful as it has class members. Fairly trivial observation.

Let’s take a look again at the previous JavaScript code.

var button = new android.widget.Button(context);
button.setOnClickListener(new android.view.View.OnClickListener({
   onClick: function() {
      // do some work

We access the button widget and call its setOnClickListener method with some argument. This means that we should have instantiated Java object which implements OnClickListener so that the button can use it later. You can find the class implementation for that object in your project platform directory


Let’s see what the actual implementation is.


public class View_OnClickListener
       implements android.view.View.OnClickListener {
  public View_OnClickListener() {

  public void onClick(android.view.View param_0)  {
    java.lang.Object[] args = new java.lang.Object[1];
    args[0] = param_0;
    com.tns.Runtime.callJSMethod(this, "onClick", void.class, args);

As we can see this class acts as a proxy and doesn’t have fields. We can call this class stateless. We don’t store information that we can use to describe its closure if any.

So, we saw that Java compiler generates classes that keep track of their closures while NativeScript generates classes that don’t keep track of their closures. This is a simple implication due to the fact the JavaScript is a dynamic language and the information of lexical scope is not enough to provide full static analysis. The full information about JavaScript closures can be obtain at run time only.

The ovals diagram I used in my previous post visualize the missing object reference to the closed object. So, now we have an understanding what happens in NativeScript runtime for Android. The current NativeScript, at the time of writing version 3.3, provides mechanism to “compensate” for the missing object references. To put it simply, for each JavaScript closure accessible from Java we traverse all reachable Java objects in order to keep them alive until the closure becomes unreachable from Java. Well, while we were able to describe the current solution in a single sentence it doesn’t mean it doesn’t have drawbacks. This solution could be very slow if an object with large hierarchy, like global, is reachable from some closure. If this is the case, the implication is that we will traverse the whole V8 heap on each GC.

Back then in 2014, when we hit this issue for the first time, we discussed the option to customize part of the V8 garbage collector in order to provide faster heap traversing. The drawback is slower upgrade cycle for V8 which means that JavaScriptCore engine will provide more features at given point in time. For example, it is not easy to explain to the developers why they can use class syntax for iOS but not for Android.

Motivation: we wanted to keep V8 customization at minimum so we can achieve relatively feature parity by upgrading V8 engine as soon as possible.

So, now we know traversing V8 heap can be slow, what else? The current implementation is incomplete and case-by-case driven. This means that it is updated when there are important and common memory usage patterns. For example, currently we don’t traverse Map and Set objects.

Let’s see what can happen in practice. Create a default app.

tns create app1

Run the app and make sure it works as expected.

Now, we have to go through the process of designing a user scenario where the runtime will crash. We know that the current implementation doesn’t traverse Map and Set objects. So, we have to make Java object which is reachable only through, let’s say, Map object. This is only the first part of our exercise. We also must take care to make it reachable through a closure. Finally, we must give a chance for GC to collect it before we use it. So, let’s code it.

function crash() {
    var m = new Map();
    m.set('o', new java.lang.Object() /* via the map only */);
    var h = new android.os.Handler(android.os.Looper.getMainLooper()); java.lang.Runnable({
        run: function() {

That’s all. Finally, we have to integrate crash within our application. We can do so by modifying onTap handler in [proj_dir]/app/main-view-model.js as follows:

viewModel.onTap = function() {
    this.set("message", getMessage(this.counter));

Run the app and click the button. You should get error screen similar to the following one.

Motivation: we wanted to evolve V8 heap traversing on case-by-case basis in order to traverse as little as possible.

Understanding this memory usage pattern (create object, set up object reachability, GC and usage) is a simple but powerful tool. With the current implementation the fix for Map and Set is similar to this one. Also, realizing that in the current implementation the missing references to the captured objects is the only reason for this error is critical for any further changes. This is well documented in the form of unit tests.

So far we discussed the drawbacks of the current implementation. Let’s say a few words about its advantages. First, and foremost, it keeps the current memory management model familiar to the existing Java and JavaScript developers. This is important in order to attract new developers. If two technologies, X and Y, solve similar problems and offer similar licenses, tools, etc., the developers are in favor for the one with simpler “mental model”. While introducing alloc/free or try/finally approach is powerful, it does not attract new developers because it sets higher entry level, less explicit approach. Another advantage, which is mostly for the platform developers, is the fact that current approach aligns well with many optimizations that can be applied. For example, taking advantage (introducing) of GC generations for the means of NativeScript runtime. Also, it allows per-application fine tuning of existing V8 flags (e.g, gc_intervalincremental_markingminor_mc, etc.). Tweaking V8 flags won’t have general impact when manual memory management is applied. In my opinion, tuning these flags is yet another way to help regular Joe shooting himself in the foot, but providing sane defaults and applying adaptive schemes very possible could be a huge win.

It is important to note that whatever approach is applied, this must be done carefully because of the risk of OOM exception. Introducing schemes like GC generation should consider the object memory weight. This will make obsolete the current approaches that use time and/or memory pressure heuristics. In general, such GC generation approach will pay off well.

I hope I shed more light on this challenging problem. Looking forward to see how the team is going to approach it. Good luck!

NativeScript release life cycle

I am glad to announce that yesterday we released NativeScript 2.4. This is all good, but in this post I would like to discuss the future. If you take a look at the next GitHub milestone you will see this


So, why 2.5.0-RC?

There are many reasons for this. Firstly, it is hard to make a feature right from the first time. And by “right” I don’t mean correct but also right from technical perspective. It’s not easy to say but every developer knows the difference a solution and the right solution. Secondly, often our requirements are incomplete and we need feedback as soon as possible in order to ship the right feature. Even with complete requirements it will take longer for development, thus delaying the user feedback. Following the analogy with minimum viable product (MVP), you can think of minimum viable technical implementation that (almost) meets the current requirements. As with many other release approaches it is a trade-off. Shipping RC is a sweet spot as we will offer reasonable product quality in a timely manner. Each RC will be followed shortly by an official release. So far, our release history shows that a week or two is enough to fix all corner-case issues and apply other minor fixes.

Of course, there are drawbacks. Probably the biggest one is that there will be increased operational costs for actual shipping RC or required changes in the test infrastructure for example. I think this is a good incentive to automate even more the existing processes and infrastructures so it will be a win-win situation. Stay tuned.

NativeScript Performance – Part 2

The last two weeks I was busy with measuring and optimizing the performance of NativeScript for Android. My main focus was the application startup time and I would like to share some good news.


Let’s first see the results and then I will dig into the details. As in the previous tests I uses the same test devices:

  • Device1 – Nexus 5, Android 4.4.1, build KOT49E
  • Device2 – Nexus 6, Android 5.0.1, build LRX22C

I used the same application as well. Here are the results:

  • For Device1 the first startup time was reduced from average 3.1419 seconds to average 2.8262 seconds (10% improvement) [*]
  • For Device2 the first startup time was reduced from average 3.541 seconds to average 3.3147 seconds (6% improvement) [*]


Before I dig into the details, I would like to give you a quick reminder how I measured the times. As in the previous tests I used the built-in time/perf info that Android ActivityManager provides. It is not the best measuring tool but it is good enough for our purposes.

After detailed profiling with DDMS and NDK profilers I identified two areas for improvements:

  • asset extraction
  • proxy property access


The old implementation for asset extraction was based on AssetManager. While its API is very convenient, it is not well suited for optimal memory allocation. As a result using AssetManager along with* classes generates a lot of temporary objects which triggers the GC quite often. The solution we chose is to use libzip C++ library. It is fast and more importantly it doesn’t mess with the GC.

For applications with size similar to the test app using libzip doesn’t help much. The actual improvement is around 30-40 milliseconds. However, for big apps (e.g. 500+ files) libzip really shines. You can easily get improvement of 300-500ms, and in some scenarios more than a second. This was a good reason to reimplement the Java code into C++ and give NativeScript the ability to scale really well.

Java Object Wrappers

Proxies are an experimental ECMAScript 6 feature. In V8 (and for the matter of fact in any other JavaScript engine), direct property access is much faster than direct proxy access. This is easily understandable when you think how the JIT compiler emits the code to access traditional properties. Also, while proxies are good for scripting simple object access they don’t scale in more complex scenarios. With the time it becomes harder to implement the correct dispatch logic.

I am glad to say that we now use plain JavaScript objects to wrap Java objects. We also build the correct prototype chain to map Java class hierarchy. This give us an excellent opportunity to cache runtime objects at more granular level. And as we are going to see, caching changes everything.

While using libzip helped a little bit, it is easy to do the math and see that using prototype chains is the main factor for the improved startup time.

Let’s see how the new caches impact other scenarios. Take a look at the following code fragment.

var JavaDate = java.util.Date;
var start = new Date();
for (var i=0; i<10000; i++) {
    var d1 = new JavaDate();
    var d2 = new JavaDate();
var end = new Date();
console.log("time=" + (end.getTime() - start.getTime()));

This is not a real world scenario. I wrote this code for sole test purposes. My intent here is to exercise some Java intensive code. Also, note that using JavaScript Date.getTime is not the best way to measure time, but as we are going to see it is good enough for our purposes.

Here are the results.

  • On Device1 – using proxy objects it takes more than 12.5 seconds, using prototype chain it takes less than 2.6 seconds
  • On Device2 – using proxy objects it takes more than 11.6 seconds, using prototype chain it takes less than 2.2 seconds

In my opinion, there is no need for any further or more precise benchmarks. Simply put, using prototype chains along with proper caching is much faster than proxy objects.

Further Improvements

So far, we saw that the first startup of a simple application like CutenessIO takes around 3 seconds. Can we make it faster?

First, we have to set some reasonable expectations. Let’s see how fast HelloWorld applications written in Java and NativeScript start up. For the Java version I used the standard Eclipse project template (which is very similar to the one in Android Studio). I stripped all things like menus and fancy themes. My main goal was the make it as simple as possible (which is not much different from the standard empty project). I did the same for the NativeScript project.

Here are the results.

  • On Device1 – Java 200 milliseconds[*], NativeScript 641.5 milliseconds[*]
  • On Device2 – Java 333.5 milliseconds[*], NativeScript 875.3 milliseconds[*]

So, we have to investigate where the difference comes from. For the purpose of this article, I am going to pick Device1 (the analysis for Device2 is the same).

Let’s analyze a particular run.

  • Time for loading libNativeScript library: 7ms
  • Time for extracting assets: 30ms
  • Time for V8 initialization: 150ms
  • Time for calling Application.onCreate in JavaScript: 60ms
  • Time for calling Activity.onCreate in JavaScript: 100ms
  • Time from Application object initialization to Activity initialization: 510ms
  • Time to display main activity: 658ms

As we can see, the total time of asset extraction and V8 initialization is 180ms which is roughly the time needed for pure Java application to start. So far, it seems unlikely to reduce this time.

The total time spent in running JavaScript 160ms. This is a bit surprising. I would love to see the time spent in V8 to be, say, 400ms because this would mean that running JavaScript is 78% (400/510) of all time. High percentage of time spent inside in V8 is a good thing because this will give us an opportunity to optimize the performance. However, this would not be the case for most applications. We can think of NativeScript as a way to command Java world from JavaScript. Hence, most of the work is done in Java. That’s the nature of NativeScript.

So, we spent 160ms running a few lines of JavaScript. Can we do better? A careful analysis showed that most of this time is spent in JNI infrastructure calls and data marshalling. It seems hard to reduce it, but not unlikely. A possible option is to tweak V8 engine and/or use libffi to generate thunks.

Another 200ms is spent in some run-once pluming code. With a little effort, we could refactor the runtime to support components/modules and gain some performance. Finally, some time is spent inside the Java GC.

In closing, I would say that currently NativeScript for Android is performing well. There are no major performance issues. The current implementation is approaching the point where no big performance wins can be easily achieved. But easy is not interesting 😉 Stay tuned.

On NativeScript Performance


Last week NativeScript made it into public beta and just for a few days we got tremendous amount of feedback. One question that came up over and over again was, “How do NativeScript Apps Perform”?  In this post, I want to explain the details behind performance and share some great news with you about the upcoming release of NativeScript.

How it started

As other new projects NativeScript started from the idea to take a new look at the cross-platform mobile development with JavaScript. In the beginning, we had to determine if the concept of NativeScript was even feasible.  Should we translate JavaScript into Java?  What about Objective-C back into JavaScript?  During this exploratory phase, we learned that the answer was actually much simpler than this thanks to the JavaScript bridge that exists for both iOS and Android.  Well, thanks to Android fragmentation, this is only partially true.  Let me explain…


Working on a project like NativeScript is anything but easy. There are many challenges imposed by working with two very different runtimes like Dalvik and V8. Add the restricted environment in Android and you will get the idea. Controlling object lifetime when you have two garbage collectors, efficient type marshalling, lack of 64bit integers in JavaScript, correctly working with different UTF-8 encodings, and overloaded method resolution, just to name a few. All these are nontrivial problems.

Statically Generated Bindings

One specific problem is the extending/subclassing of Java types from JavaScript. It is astonishing how a simple task like working with a UI widget becomes a challenging technical problem. It takes no longer to look than the Button documentation and its seemingly innocent example.

button.setOnClickListener(new View.OnClickListener() {
    public void onClick(View v) {
        // Perform action on click

While the Java compiler is there for you to generate an anonymous class that implements View.OnClickListener interface there is no such facility in JavaScript. We solved this problem by generating proxy classes (bindings). Basically we generated *.java source files, compiled them to *.class files which in turn were compiled to *.dex files. You can find these *.dex files in assets/bindings folder of every NativeScript for Android project. The total size of these files is more than 12MB which is quite a lot.

Here begins the interesting part. Android 5 comes with a new runtime (ART). One of major changes in ART is the ahead-of-time (AOT) compiler. Now you can imagine what happens when the AOT compiler has to compile more than 12MB *.dex files on the very first run of any NativeScript for Android application. That’s right, it takes a long time. The problem is less apparent in Android 4.x but it is still there.

Dynamically Generated Bindings

The solution is obvious. We simply need to generate bindings in runtime instead of compile time. The immediate advantages are that we will generate bindings only for those classes that we actually extend in JavaScript. Lesser the bindings, lesser the work for the AOT compiler.

We started working on the new binding generator right after the first private beta. We were almost done for the public beta. However, almost doesn’t count. We decided to play safe and release the first beta with statically generated bindings. The good news is that the new binding generator is already merged in the master branch (only two days after the public beta announcement).

Today I ran some basic performance tests on the following devices:

  • Device1 – Nexus 5, Android 4.4.1, build KOT49E
  • Device2 – Nexus 6, Android 5.0.1, build LRX22C

For the tests I used the built-in time/perf info that Android OS provides. You probably have seen similar information in your logcat console.

I/ActivityManager(770): START u0 {act=android.intent.action.MAIN cat=[android.intent.category.LAUNCHER] flg=0x10200000 cmp=com.tns/.NativeScriptActivity} from pid 1030
I/ActivityManager(770): Displayed com.tns/.NativeScriptActivity: +3s614ms

Here are the results:

  • For Device1 the first start-up time was reduced from average 60.761 seconds to average 3.1419 seconds
  • For Device2 the first start-up time was reduced from average 39.384 seconds to average 3.541 seconds

A consequential start-up time for both devices is ~2.5 or less seconds.

What’s next

There is a lot of room for performance improvement. Currently NativeScript for Android uses JavaScript proxy object to get a callback when Java field is accessed or Java method is invoked. The problem is that proxy objects (interceptors) are not fast. We plan to replace them with plain JavaScript objects that have properly constructed prototype chain with accessors instead of interceptors. Another benefit of using prototype chains with accessors is that we will support JavaScript instanceof operator.

Another area for improvement is the memory management. Currently, we generate a lot of temporary Java objects which may kick the Java GC unnecessary often. Moving some parts of the runtime from Java to C++ is a viable option that we are going to explore.


In closing, I would like to say that we are astounded by how popular NativeScript has become in such a short amount of time. We have learned so much in the building the NativeScript runtime, and our experience in that process helps us improve NativeScript every single day.  We’re looking forward to version 1. Building truly native mobile applications with native performance using JavaScript is the future, and the future is now.

Java Class Inheritance in NativeScript for Android

One of the more advanced scenarios in NativeScript for Android is the inheritance of Java classes. Let’s take a look at the following example.

// app.js
var MyButton = android.widget.Button.extend({
    setEnabled: function(enabled) {
        // do something
var btn = new MyButton(context);

(Please note that at the time of writing NativeScript is in private beta version and the syntax may change in the future.)

This is a minimalistic example how to define a new derived class with JavaScript. In this example we define new class MyButton that inherits from android.widget.Button and overrides setEnabled method. Behind the scenes NativeScript for Android will generate a new Java class as follows.

public class <runtime_generated_name> extends android.widget.Button {
    public void setEnabled(boolean enabled) {
        Object[] params = new Object[1];
        params[0] = enabled;
        NativeScriptRuntime.callJSMethod(this, "setEnabled", params);

This class serves as a simple proxy that calls the JavaScript implementation of setEnabled method. For the curious ones the method callJSMethod is defined as native and is used to dispatch the method invocation to the JavaScript engine.

public class NativeScriptRuntime {
    public static native Object callJSMethod(Object obj, String methodName, Object[] params);

So far we didn’t talk about the class’ <runtime_generated_name>. This name is generated from the following things:

  • the name of the base class
  • the name of the JavaScript file in which the class is defined
  • the line number
  • the column number

Let’s assume that MyButton is defined in app.js file on line 21 and column 38. In this case the generated class name may be something like <package_prefix>.android_widget_Button_app_L21_C38 where <package_prefix> is some hard-coded package name.

For more advanced scenarios NativeScript for Android allows you to overwrite the generated class name. You can do that using the full extend signature.

extend(<class_name>, implementationObject)

Usually you can omit class_name argument and let NativeScript to generate it for you.

There is one important difference between Java and JavaScript though. Java generates derived classes at compile time while NativeScript generates derived classes at runtime. As a consequence Java generates a derived class exactly once while NativeScript can execute extend function multiple times. This means that NativeScript must performs validation checks before it generates a class.

There are many approaches to this problem. As NativeScript for Android is in private beta we are still discussing what the validation checks should be. Here is a simplified diagram of one possible approach.


We basically can check whether extend is called with the same name and implementation object before and return the cached class. In this case it seems reasonable to freeze the implementation object on the first call in order to guarantee that multiple instances of a single extended class will have the same runtime behavior.

In closing, I would like to say that there is not much time until the official release of NativeScript. Today I showed you just one possible approach how to extend a Java class from JavaScript. There are other options as well. If you think there are better solutions please do not hesitate and leave a comment.