Efficient IO in Android

What could be simpler than a file copy? Well, it turned out that I underestimated such an easy task.

Here is the scenario. During the very first NativeScript for Android application startup the runtime extracts all JavaScript asset files to the internal device storage. The source code is quite simple and it was based on this example.

static final int BUFSIZE = 100000;

private static void copyStreams(InputStream is, FileOutputStream fos) {
    BufferedOutputStream os = null;
    try {
        byte data[] = new byte[BUFSIZE];
        int count;
        os = new BufferedOutputStream(fos, BUFSIZE);
        while ((count = is.read(data, 0, BUFSIZE)) != -1) {
            os.write(data, 0, count);
    } catch (IOException e) {
        Log.e(LOGTAG, "Exception while copying: " + e);
    } finally {
        try {
            if (os != null) {
        } catch (IOException e2) {
            Log.e(LOGTAG, "Exception while closing the stream: " + e2);

It is important to note the in our code BUFSIZE constant has value 100000 while in the original example the value is 5192. While this code works as expected it turns out it is quite slow.

In our scenario we extract around 200 files and on LG Nexus 5 device it takes around 5.75 seconds. This is a lot of time. It turned out that most of this time is spent inside the garbage collector.

D/dalvikvm(8611): GC_FOR_ALLOC freed 265K, 2% free 17131K/17436K, paused 8ms, total 8ms
D/dalvikvm(8611): GC_FOR_ALLOC freed 398K, 4% free 16930K/17636K, paused 11ms, total 11ms
D/dalvikvm(8611): GC_FOR_ALLOC freed 197K, 4% free 16930K/17636K, paused 7ms, total 7ms
... around 650 more lines

The first thing I optimized was to make data variable a class member.

static final int BUFSIZE = 100000;

static final byte data[] = new byte[BUFSIZE];

private static void copyStreams(InputStream is, FileOutputStream fos) {
   // remove 'data' local variable

I thought this will solve the GC problem but when I ran the application I was greeted with the following familiar log messages.

D/dalvikvm(8408): GC_FOR_ALLOC freed 248K, 2% free 17212K/17496K, paused 7ms, total 8ms
D/dalvikvm(8408): GC_FOR_ALLOC freed 417K, 4% free 17029K/17696K, paused 8ms, total 8ms
D/dalvikvm(8408): GC_FOR_ALLOC freed 199K, 4% free 17029K/17696K, paused 7ms, total 7ms
... around 330 more lines

This time it took around 2.25 seconds to extract the files. And the GC kicked 330 times instead of 660 times. Well, it was better but it wasn’t what I wanted. The GC kicked twice less than the previous example but still it was too much.

The next thing I tried is to set BUFSIZE to 4096 instead of 100000.

static final int BUFSIZE = 4096;

This time it took around 0.85 seconds to extract the assets and the GC kicked 8 times.

D/dalvikvm(8218): GC_FOR_ALLOC freed 323K, 3% free 17137K/17496K, paused 8ms, total 8ms
D/dalvikvm(8218): GC_FOR_ALLOC freed 673K, 5% free 16947K/17684K, paused 8ms, total 9ms
D/dalvikvm(8218): GC_FOR_ALLOC freed 512K, 5% free 16947K/17684K, paused 8ms, total 9ms
... just 5 more lines

It was a nice improvement but I thought it should be faster than this. I was still puzzled with this relatively high level of GC activity so I decided to read the online documentation.

A specialized OutputStream for class for writing content to an (internal) byte array. As bytes are written to this stream, the byte array may be expanded to hold more bytes.

I’ve should read this before I start. It was a good lesson to me.

Once I knew what happens inside BufferedOutputStream internals I decided just not to use it. I call write method of FileOutputStream and voilà. The time to extract the assets is around 0.65 seconds and the GC kicks 4 times at most.

Out of curiosity I decided to try to bypass the GC using libzip C library. It took less than 0.2 seconds to extract the assets. Another option is to use AAssetManager class from NDK but I haven’t tried it yet. Anyway, it seems that IO processing is one of those areas where unmanaged code outperforms Java.

First Impressions using Windows 10 Technical Preview for phones

Windows 10 Technical Preview for phones was released two days ago and today I decided to give it a try. The installation process on my Nokia 630 was very smooth and completed for about 30 minutes including the migration of the old data. Finally, I ended up with WP10 OS version 9941.12498.


After I used WP10 for about 6 hours I can say that this build is quite stable. The UI and all animations are very responsive. So far I didn’t experience any crashes. The only glitch I found is that the brightness setting is not preserved after restart and it is set automatically to HIGH. All my data including photos, music and documents were preserved during the upgrade.

There are many productivity improvements in WP10. Action Center and Settings menu are much better organized. It seems that IE can render some sites better than before though I am not sure if it is the new IE rendering engine or just the site’s html has been optimized.

I checked to see whether there are changes in Chakra JavaScript engine but it seem the list of exported JsRT functions is the same as before. The actual version of jscript9.dll is 11.0.9941.0 (fbl_awesome1501.150206-2235).

I tested all of my previously installed apps (around 60) and they all work great. The perceived performance is the same, except for Lumia Panorama which I find slower and Minecraft PE which I find faster.

There are many new things for the developers as well. I guess one of the most interesting changes in WP10 is the improved speech support API. Using the speech API is really simple.

using Windows.Phone.Speech.Synthesis;

var s = new SpeechSynthesizer();
s.SpeakTextAsync("Hello world");

WP10 comes with two predefined voice profiles.

using using Windows.Phone.Speech.Synthesis;

foreach (var vi in InstalledVoices.All)
    var si = new SpeechSynthesizer();
    await si.SpeakTextAsync(vi.Description);

The actual values of vi.Description are as follows.

Microsoft Zira Mobile - English (United States)
Microsoft Mark Mobile - English (United States)

You can hear how Zira and Mark actually sound below.

I find Mark’s voice a little bit more realistic.

This is all I got for today. In closing I would say it seems that WP10 has much more to offer. Stay tuned.

Embedding Chakra JavaScript Engine on Windows Phone

Today I am going to show you how to embed Chakra JavaScript engine in Windows Phone 8.1 app. Please note that at the time of writing this app won’t pass Microsoft Windows Store certification requirements. I won’t be surprised though if Microsoft reconsider their requirements in future.

Last year Microsoft released JsRT which exposes C-style API for embedding Chakra JavaScript engine. To use the API you only need to include jsrt.h and add a reference to jsrt.lib. On my machine the header file is located at

C:\Program Files (x86)\Windows Kits\8.1\Include\um\jsrt.h

and the lib files (for x86 and x64 accordingly) are located at

C:\Program Files (x86)\Windows Kits\8.1\Lib\winv6.3\um\x86\jsrt.lib
C:\Program Files (x86)\Windows Kits\8.1\Lib\winv6.3\um\x64\jsrt.lib

Curiously, there is no jsrt.lib for ARM architecture. It is even more interesting that JsRT is not exposed in Windows Phone SDK. E.g. you won’t find jsrt.h file in

C:\Program Files (x86)\Windows Phone Kits\8.1\Include

neither you will find jsrt.lib in

C:\Program Files (x86)\Windows Phone Kits\8.1\lib\ARM
C:\Program Files (x86)\Windows Phone Kits\8.1\lib\x86

However this shouldn’t discourage us. The first thing we should check is that JsRT API is exposed on Windows Phone 8.1. I know it is there because IE11 shares same source code for desktop and mobile and because Windows Phone 8.1 supports WinRT programming model. Anyway, let’s check it.

Find flash.vhd file. On my machine it is located at

C:\Program Files (x86)\Microsoft SDKs\Windows Phone\v8.1\Emulation\Images

Use Disk Management and attach flash.vhd file via Action->Attach VHD menu. Navigate to \Windows\System32 folder on MainOS partition and copy JSCRIPT9.DLL somewhere. Open Visual Studio command prompt and run the following command

dumpbin /exports JSCRIPT9.DLL >jscript9.def

Open jscript9.def file in your favorite editor and make sure you see the full JsRT API listed here. Edit the file so it becomes like this one https://gist.github.com/anonymous/88e44e8931cc8d118da9. Run the following command from the Visual Studio command prompt

lib /def:jscript9.def /out:jsrt.lib /machine:ARM

This will generate import library so you can use all exports defined in JSCRIPT9.DLL library. We are almost ready.

We generated jsrt.lib import library for ARM architecture, what’s next? In order to use jsrt.h header in our Windows Phone 8.1 project we must edit it a little bit. First copy it and its dependencies to your project. Here is the list of all the files you should copy

  • activdbg.h
  • activprof.h
  • ActivScp.h
  • DbgProp.h
  • jsrt.h

In case you don’t want JavaScript debugging support you can copy jsrt.h file only and replace all pointers to the interfaces from ActiveScript API with void*. Once you copy the the header files you must edit them to switch to Windows Phone API. To do so, you have to replace WINAPI_PARTITION_DESKTOP with WINAPI_PARTITION_PHONE_APP. It may sound like a lot of work but it is just a few lines change. You can see the change here.

That’s it. Now you can use the new header and lib files in your project. You can find the full source code at https://github.com/mslavchev/chakra-wp81.

In closing I would like to remind you that at present this app won’t pass Windows Store certification requirements. Here is the list of the requirement violations

Supported API test (FAILED)
    This API is not supported for this application type - Api=CoGetClassObject. Module=api-ms-win-core-com-l1-1-1.dll. File=ChakraDemoApp.exe.
    This API is not supported for this application type - Api=JsCreateContext. Module=jscript9.dll. File=ChakraDemoApp.exe.
    This API is not supported for this application type - Api=JsCreateRuntime. Module=jscript9.dll. File=ChakraDemoApp.exe.
    This API is not supported for this application type - Api=JsDisposeRuntime. Module=jscript9.dll. File=ChakraDemoApp.exe.
    This API is not supported for this application type - Api=JsRunScript. Module=jscript9.dll. File=ChakraDemoApp.exe.
    This API is not supported for this application type - Api=JsSetCurrentContext. Module=jscript9.dll. File=ChakraDemoApp.exe.
    This API is not supported for this application type - Api=JsStartDebugging. Module=jscript9.dll. File=ChakraDemoApp.exe.
    This API is not supported for this application type - Api=JsStringToPointer. Module=jscript9.dll. File=ChakraDemoApp.exe.

Hopefully Microsoft will revisit their requirements.

Running JavaScriptCore on Windows Phone 8.1

After the first release of NativeScript I decided to spend some time playing with JavaScriptCore engine. We use it in NativeScript bridge for iOS and so far I heard good words about it from my colleagues. So I decided to play with JavaScriptCore and compare it to V8 engine.

At present NativeScript supports Android and iOS platforms only. We have plans to add support for Windows Phone as well and I thought it would be nice to have some experience with JavaScriptCore on Windows Phone before we make a choice between Chakra and JavaScriptCore.

The first difference I noticed between JavaScriptCore and V8 is that it has an API much closer to C style while the V8 API is entirely written in C++. This is not an issue and sometimes I consider it as an advantage.

The second difference, in my opinion, is that JavaScriptCore API is more simpler and expose almost no extension points. From this point of view I consider the V8 API the better one. Compared to JavaScriptCore, V8 provides much richer API for controlling internals of the engine like JIT compilation, object heap management and garbage collection.

Nevertheless it was fun to play with JavaScriptCore engine. You can find a sample project at GitHub.

Java and V8 Interoperability

The project I currently work on involves a lot of Java/JavaScript (V8 JavaScript engine) interoperability. Fortunately, Java provides JNI and V8 has a nice C++ API which make the integration process very smooth. Most of the Java-JNI-V8 type marshaling is quite straightforward but there is one exception.

The JNI uses modified UTF-8 strings to represent various string types. Modified UTF-8 strings are the same as those used by the Java VM. Modified UTF-8 strings are encoded so that character sequences that contain only non-null ASCII characters can be represented using only one byte per character, but all Unicode characters can be represented.

I was well aware of this fact since the beginning of the project but somehow I neglected it. Until recently, when one of my colleagues showed me a peculiar bug that turned out to be related to the process of marshaling a non-trivial Unicode string.

At first, I tried a few quick and dirty workarounds just to prove that the root of problem is more complex it seemed. Then I realized that jstring type is not the best type when it comes to string interoperability with V8 engine. I decided to use jbyteArray type instead of jstring though I had some concerns about the performance overhead.

private static native void doSomething(byte[] strData);

String s = "some string";
byte[] strData = s.getBytes("UTF-8");

The code doesn’t look ugly though the string version looks better. I did microbenchmarks and it turned out the performance is good enough for my purposes. Nevertheless, I decided to compare the performance with Nashorn JavaScript engine. As expected, Nashorn implementation was faster because it uses the same internal string format as the JVM.

On Agile Practices

I have recently read the article What Agile Teams Think of Agile Principles from Laurie Williams and it got me thinking. The study conclusion is as follows:

The authors of the Agile Manifesto and the original 12 principles spelled out the essence of the agile trend that has transformed the software industry over more than a dozen years. That is, they nailed it.

Here are the top 10 agile practices from the case study.

Agile practice Mean Standard Deviation
Continuous integration 4.5 0.8
Short iterations (30 days of less) 4.5 0.8
“Done” criteria 4.5 0.8
Automated tests run with each build 4.4 0.9
Automated unit testing 4.4 0.9
Iterations review/demos 4.3 0.8
“Potentially shippable” features at the end of each iteration 4.3 0.9
“Whole” multidisciplinary team with one goal 4.3 0.8
Synchronous communication 4.4 0.9
Embracing changing requirements 4.3 0.8

These are indeed practices instead of exact science and I am going to elaborate more on this topic. But first I would like to recap a few things from the history of the software industry.

Making successful software is hard. Many software projects failed in the past and many software projects are failing now. There are a lots of studies that confirm it. Some studies claim that more than 50% of all software projects fail. In order to improve the rate of successful projects we tried to adopt know-how from other industries. The software industry adopted metaphors like building software and software engineering. We started to apply waterfall methodologies and rigorous scientific methods for defining software requirements like UML. We tried many things in order to do better software but not much changed.

Then people came up with the idea of agile software methodology. Agile manifesto states:

  • Individuals and interactions over processes and tools
  • Working software over comprehensive documentation
  • Customer collaboration over contract negotiation
  • Responding to change over following a plan

Agile methodology proposes different mindset. We started put emphasis on things like creativity and self-organizing teams more than engineering. Nowadays, we use metaphors like writing software much more often than 15 years ago. Some people go further by comparing programmers with writers and consequently in order to do good software we need good writers instead of good engineers. While I find such claims a bit controversial they are many people who share similar opinions. In general, today we talk about software craftsmanship instead of software engineering.

These two approaches are not mutually exclusive. I see good trends of merging both of them whenever it is reasonable. It is natural for people to select the best from both worlds. Still, agile methodology is considered young. Most of the software companies still publish their job offerings as “Software Engineer Wanted” instead of “Software Craftsman Wanted“. This is only one example of what we have inherited in IT industry. It does not matter how much an IT company boasts how agile it is, the fact is that we need time to fully adopt the new mindset. The good thing is that the new mindset focuses on the individual and I think this is the key for better software.

ECMAScript 262 And Browser Compatibility

I was curious to check how well the current browsers implement ECMAScript 262 specification. At the time of writing I have the following browsers installed on my machine:

  • Google Chrome (34.0.1847.116 m)
  • Microsoft IE (11.0.9600.17031 / 11.0.7)
  • Mozilla Firefox (28.0)

I guess Chrome, IE and Firefox present at least 90% of all desktop browsers. I tested them against the test suite provided by ECMA (http://test262.ecmascript.org) and it turned out none of them passed all the tests. Here is the list of failing tests for each browser.

I know that some of the smartest guys in IT work on these projects for many years. So, the next time I hear that JavaScript is a simple scripting language I won’t consider it seriously.

Native code profiling with JustTrace

The latest JustTrace version (Q1 2014) has some neat features. It is now possible to profile unmanaged applications with JustTrace. In this post I am going to show you how easy it is to profile native applications with JustTrace.

For the sake of simplicity I am going to profile notepad.exe editor as it is available on every Windows machine. First, we need to setup the symbol path folder so that JustTrace can decode correctly the native call stacks. This folder is the place where all required *.pdb files should be.


In most scenarios, we want to profile the code we wrote from within Visual Studio. If your build generates *.pdb files then it is not required to setup the symbols folder. However, in order to analyze the call stacks collected from notepad.exe we must download the debug symbols from Microsoft Symbol Server. The easiest way to obtain the debug symbol files is to use symchk.exe which comes with Microsoft Debugging Tools for Windows. Here is how we can download notepad.pdb file.

symchk.exe c:\Windows\System32\notepad.exe /s SRV*c:\symbols*http://msdl.microsoft.com/download/symbols

[Note that in order to decode full call stacks you may need to download *.pdb files for other dynamic libraries such as user32.dll and kernelbase.dll for example. With symchk.exe you can download debug symbol files for more than one module at once. For more details you can check Using SymChk page.]

Now we are ready to profile notepad.exe editor. Navigate to New Profiling Session->Native Executable menu, enter the path to notepad.exe and click Run button. Once notepad.exe is started, open some large file and use the timeline UI control to select the time interval of interest.


In closing, I would say that JustTrace has become a versatile profiling tool which is not constrained to the .NET world anymore. There are plenty of unmanaged applications written in C or C++ and JustTrace can help to improve their performance. You should give it a try.

501 Must-Write Programs

In the spirit of 501 Must-Visit… book series I decided to write this post. My ambitions are much smaller so don’t expect a comprehensive “guide” to computer programming. Nevertheless, I just think it would be useful to show you short programs that demonstrate important computer ideas and techniques.

Fortunately, as software developers, we don’t need to know 501 things in order to accomplish our daily tasks. So my intention is write a list of programs with brief explanation for each one. I will extend the list whenever I find programs good enough to represent important computer techniques. At first sight, the programs in the list may seem random or unusual but they all demonstrate important aspects of commonly used concepts in computer programming. Here goes the first ten in no particular order:

  1. Nth Fibonacci number  – I know, I know… it is too simple. However, I think we often can learn from simple things. Let’s see what there is for us to learn. Fibonacci numbers are one of the canonical examples for recursion. They can be used to explain time complexity in a very easy manner as well. It’s also good to mention Binet’s formula and memoization technique.
  2. Conway’s Game of Life – I include this program in the list just because it is beautiful. It is an excellent example of how simple rules can lead to complex interaction. Cellular automation is used in computability theory, mathematics, physics, complexity science and theoretical biology just to mention a few. To the curious readers, I recommend to read about Wolfram code as well.
  3. Quine (self-replicating program) – It is really fun to write a quine in your favorite (Turing complete) programming language. While writing a quine program is fun and good for your creativity, it is worthy to note its deep connection with mathematical logic and fixed point in mathematics.
  4. Currency converter – While this program may not seem fun or a programming challenge, it’s a handy tool and it will make you familiar with units of measure concept which is important in numeric calculation.
  5. String searching – I guess this is one of most common tasks in our work. Every now and then we have to search for a given substring. While the naive implementation is easy to write, you will quickly find out that it is impractical for large strings due its time and space complexity. Then you will enter the wonderful world of Knuth–Morris–Pratt and Rabin–Karp string search algorithms. There are tons of scientific literature on the topic and most of it comes from bioinformatics and computational mathematics.
  6. Huffman coding – It is, by far, the easiest introduction into the information theory and lossless data compression. While nowadays there are much better data compression algorithms, the idea of Shannon entropy is still used.
  7. Line counting – Well, you may find this is too lame. Counting the lines of a text file is not a big deal until the file is small and can fit into the main memory. Then you quickly come with the idea of data buffer. While buffering is not a rocket science it is one of most practical and useful things in most code bases.
  8. Calculate definite integral – Yes, you read it right. At first you may wonder how calculus is related to computer programming. I chose this relatively simple program because it demonstrates important ideas used in numerical analysis such as approximation and sampling. Both ideas are very important in computer programming because everything in computer science is discrete in a broader sense. If your programming languages allows passing functions as parameters then you can write this program in functional programming style.
  9. Graph traversal – Graphs are one of the most commonly used data structures. While both depth-first search and breadth-first search algorithms are easy to understand, together they represent a duality which is common to find in the computer science.
  10. Tic-tac-toe game – Writing this game is one of the easiest introduction to game theory. The simplicity of the game allows you to comprehend hard ideas like NP-complete and NP-hard problems, backtracking algorithms, alpha-beta pruning and minmax rule.