Download A Study on the Android-to-iOS Smart Game Content

International Journal of Software Engineering and Its Applications
Vol.8, No.9 (2014), pp.1-16
http://dx.doi.org/10.14257/ijseia.2014.8.9.01
A Study on the Android-to-iOS Smart Game Content Converter
JaeHyun Kim1 and YangSun Lee1*
1
Dept. of of Computer Engineering, Seokyeong University
16-1 Jungneung-Dong, Sungbuk-Gu, Seoul 136-704, KOREA
[email protected], *[email protected]
Abstract
Mobile communication companies choose different smart phone platforms, so that game
developers must create content designed specifically for each platform or use a conversion
process to provide game content to consumers. In this paper, to resolve this problem, the
Android-to-Ios smart game converter was designed to automatically convert game contents
from the Android platform to the iOS platform for smart phones using a content analyzer, a
resource converter, a platform mapping engine and a source translator. The Android
platform developed by Google is an optimized platform for mobile devices with a perfect
combination of an operating system, middleware, and application programs. The iOS
platform developed by Apple is the world’s most advanced mobile operating system,
continually redefining what people can do with a mobile device. Through the Android-to-iOS
converter, resources such as images and sounds can be converted, APIs can be converted
using a platform mapping engine and game sources can be converted using a source
translator with compiler writing technology. Experimental results indicate that the graphics,
image output, sound output, and other functions of converted iOS games were equivalent to
those of the Android games before conversion.
Keywords: Android-to-iOS Converter, Automatic Smart Game Converter, Android, iOS,
Content Analyzer, Resource Converter, Platform Mapping Engine, Source Translator
1. Introduction
The Android platform developed by Google is an optimized platform for mobile
devices with a perfect combination of an operating system, middleware, and application
programs [1-3].The iOS platform developed by Apple is the world’s most advanced
mobile operating system, continually redefining what people can do with a mobile
device [4-6].In the mobile market, the appearance of various smart phone platforms such as
Android, iOS, Windows Phone has forced game developers to develop the same game content
repeatedly in order to ensure compatibility with each of the available platforms. Furthermore,
each game developed on the one smart phone platform must be recreated for another smart
phone platform. Consequently, considerable time and expense are being invested to analyze
and convert the sources and resources of one smart game’s content for use on the smart phone
platform [7-16].
In this paper, to resolve this problem, the Android-to-iOS automatic smart game converter
system was designed to automatically translate game content from the Android platform to
the iOS platform for smart phones using a content analyzer, a resource converter, a platform
mapping engine, and a source translator [7-16].The content analyzer analyzes the content
*
Corresponding Author
ISSN: 1738-9984 IJSEIA
Copyright ⓒ 2014 SERSC
International Journal of Software Engineering and Its Applications
Vol.8, No.9 (2014)
that is input, and produces an output in which the resource data and source code stored
within the content are separated. The resource converter is a system which converts the text
or binary resource data from the game to be converted into image, sound and user data so that
it can be used on the target platform’s file system. The platform mapping engine is a system
which provides API functions which allow the previous platform’s execution environment to
be recreated using the target platform’s wrapper functions [8, 10, 15, 16]. It supports that
they can be run in the same form and so that the converted source codes can be easily
understood and altered. In addition, it ensures the reliability and stability of execution
from homogeneity of the driving environment. The source translator receives the
Android source codes that have been produced by the contents analyzer and translates it
into iOS source codes that are semantically equivalent and carry out the same function
on the Android platform [8, 11-12, 14].
By automatically converting the existing smart game content to the other smart phone
game content, the existing smart game content can be ported quickly to a different platform.
As a result, the reusability will be increased, and the labor, time, and cost will be reduced.
2. Related Studies
2.1. Android
The Android platform developed by Google is an optimized platform for mobile
devices with a perfect combination of an operating system, middleware, and application
programs. The Android platform adopted an open source policy, and it consists of the
Linux kernel, library, run-time environment, application framework, and applications.
Figure 1 depicts the Android platform's hierarchical structure and components.
Figure 1. Android Platform's System Configuration
The Linux kernel uses core system services such as Linux version 2.6, which
includes security, memory management, process management, a network stack, and a
driver model. The kernel functions as an abstraction layer between the hardware and the
software. The library consists of C and C++ and provides a C system library, media
library, 3D library, and more. The application framework is a package component
consisting of Java; applications can be created using the packages of this framework.
All application programs for the Android platform are created using Java and
converted into class files through the Java compiler. After once conversion again into
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Dalvik Executable (DEX) files, they are executed using the Dalvik virtual machine [13].
2.2. iOS
The iOS platform developed by Apple is the world’s most advanced mobile operating
system, continually redefining what people can do with a mobile device. Together, the
iOS SDK and Xcode IDE make it easy for developers to create . Technologies shared
between iOS and OS X includes the OS X kernel, BSD sockets for networking, and
Objective-C and C/C++ compilers for native performance. Figure 2 shows a system
configuration of the iOS Platform.
Figure 2. The iOS Platform's System Configuration
The iOS platform's bottom layer is the Core OS, which is the foundation of the operating
system. It is in charge of memory management, the file system, networking, and other OS
tasks, and it interacts directly with the hardware. The Core OS layer consists of components
such as the following: OS X kernel, Mach 3.0, BSD, sockets, security, power management,
keychain, certificates, file system, and bonjour. The Core Services layer provides an
abstraction over the services provided in the Core OS layer. It provides fundamental access to
iPhone OS services and consists of the following components: collections, address book,
networking, file access, SQLite, core location, net services, threading, preferences, and URL
utilities. The Media layer provides multimedia services that you can use in your iPhone and
iPad applications.It consists of the following components: core audio, OpenGL, audio mixing,
audio recording, video playback, JPG, PNG, TIFF, PDF, quartz, core animation, and OpenGL
ES.
The Cocoa Touch layer provides an abstraction layer to expose the various libraries for
programmingthe iPhone and iPad, such as the following: multi-touch events, multi-touch
controls, accelerometer, view hierarchy, localization, alerts, web views, people picker, image
picker, and controllers [4-6].
2.3. Existing Mobile Game Converters
To date, despite the very active mobile market, there has been a lack of research on
mobile content converters, so there are few examples to which we can refer.
Furthermore, converters for existing content generally only allow conversion of content
having a similar programming language environment or do not allow automatic
conversion at all. The reality is that programmers must convert content by hand.
An existing feature phone mobile game content converter using XML has attempted
to convert Java content [17-20]. In addition, the functions of the API used in the source
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code to be converted were imitated and redefined using wrapper functions. Therefore,
there is no need to convert the source code if the same functions are used. The mutual
conversion of BREW C and WIPI C [21] and the conversion GVM C into BREW C [22]
have been examined; however, these studies were flawed because the source code was
not automatically converted, so users had to intervene and convert it manually.
On the other hand, studies of automatic conversion of mobile game content using a
compiler writing system [23-24] have been attempted. A method of increasing the
reusability of game content and enhancing productivity by converting the mobile C
content of the GVM platform into WIPI C, Java, or MIDP Java has been suggested in
feature phone [7]. In addition, other studies are underway to convert existing mobile
game content for use in the growing smart phone market for operating systems such as
Android, iOS and Windows Phone [8-14], for example, GNEX-to-Android converter [8],
GNEX-to-iOS converter [9], the WIPI-to-Windows Mobile converter [10], the WIPI-toiOS converter [11], WIPI-to-Android source converter [12,14], iOS-to-Android converter[15],
iOS-to-Bada converter [16], Android-to-iOS converter system.
3. The Android-to-iOSAutomatic Smart Game Converter
The Android-to-iOS automatic smart game converter receives Android game content in
source form and converts it into the source form that is run on the iOS platform. Figure 3
shows a model of the Android-to-iOS automatic smart game content converter system.
Figure 3. The Android-to-iOSSmart Game Converter System
For automatic conversion on the source level, first the source code must be converted into
source code for the subject platform that executes the same action. Other data such as images
and sound must also be converted into a form that can be used on the new target platform. In
addition, an API library must be provided in order to maintain equivalent programming and
event environments [7-14].
3.1 Content Analyzer
The content analyzer [7-11, 13] is a system that analyzes the content that is input, and
produces an output in which the resource data and source code stored within the content are
separated. Thus, the content analyzer must separate the image or sound resource data, in the
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form of variables, according to the variable. The Android content analyzer receives the
Android content as an input and analyzes it so that it can be easily converted into content for
the iOS platform. Then it divides the files into source files, resource files, and other files.
Figure 4 shows a model of the Android game content analyzer.
Figure 4. The Android Game Content Analyzer
Figure 5 shows the result of the content analyzer. The content analyzer contains copies of
all the files within the original folder in order to prevent changes to the original files, and then
categorizes the files as described above.
Figure 5. Android Game Content Analyzer’s Screenshot
3.2. Resource Converter
The resource converter [7-9, 13, 15-16] is a system that converts the resource data, which
is in text or binary form, into image data, sound data, and user data for use in the target
platform's file system. The image file formats used in each platform (e.g., BMP, PNG, JPEG),
sound formats (e.g., WAV, MP3, MMF), and user data must be researched and converted for
use in the target platform.Thus, the image file formats provided in existing mobile platforms
and sound file formats can all be used in the Android and iOS smart phone platforms.
Therefore, they can be produced without any conversion of text-form binary files or sound
file formats in the Android-to-iOS resource converter. Consequently, only a management file
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must be created to show which resources have been used. Figure 6 shows a model of the
resource converter system.
Figure 6. Android-to-iOSResource Converter Model
After converting the resources, the resource converter checks each of these resource file
names and makes these changes, or changes special text into an alternative. Figure 7 shows
the result of the resource converter.
Figure 7. Android-to-iOS Resource Converter’s Screenshot
3.3. Platform Mapping Engine
The platform mapping engine [7-11, 15-16] creates an execution environment on the
Android platform that is identical to that in iOS so that the same environments can be
executed identically. Thus, iOS contents are enabled to run in its original form on the Android
platform. On the basis of the created execution environment, a wrapper function format is
provided that enables identical execution of iOS's API on the Android platform. The
translated program by the source translator cannot be run on the Android platform right away.
First, Android's APIs, system variables, and system environment used in the source code must
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be converted into or matched with formats that can be used on the iOS platform. Figure 8
shows the structure of the platform mapping engine.
Figure 8. Android-to-iOS’s Platform Mapping Engine Model
3.4.1. System Environments
In Android, it has six life cycle steps: Created(onCreate()), Started(onStart()),
Resumed(onResume()), Paused(onPause()), Stopped(onStop()) and Destoryed(onDestroy()).
Each time a stage is changed, corresponding methods are called respectively. The iOS
program’s life cycle is divided into five steps: Not running, Inactive, Active, Background and
Suspended. Each step is a step in the application’s life cycle and each time a change is made,
application Will Terminate, application did Finish Launching With Options, application Did Become
Active and application Did Enter Background, and application Will Resign Active, methods are called
respectively.
In this paper, these points were put into consideration and the Android platform’s system
environment was matched one on one to the iOS platform’s system environment. For
example, an Android’s on Create and an iOS’s application did Finish Launching with Options
have a similar role? Therefore, when the on Create method in Android is called for, it calls
the application did Finish Launching with Options method in iOS. Figure 9 shows how the
Android and the iOS programs' life cycles are mapped.
3.4.2. Graphic Environments
In Android, the image is called as a Bitmap, received as a Canvas and uses on Draw to
draw in View. The set Context View method is used to put in Activity and it is called by
Intent to display the graphic on the device screen. Also in iOS, the UI Application class
which manages all the programs is initialized to Window by delegate and a UI View is put on
top so that the graphic is implemented on the UI View. The iOS image is output by assigning
the image as a Bitmap and the CG Context image is output. At this point, the UI View
receives CG Context and draws everything that is displayed on the screen in the draw Rect
section. Figure 10 and 11 shows the LCD output methods of Androidand iOS, respectively.
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Figure 9. System Mapping between Android and iOS
Figure 10. Android's Graphic Output Method
Figure 11. iOS's Graphic Output Method
3.4.3. Library Functions (APIs)
Android's API functions were designed using iOS's APIs to have the same name and thus
carry out equivalent actions. Android's classes and methods are provided using the library
package, and if any of the classes or methods is necessary, the package may be imported for
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use. The translated iOS source code shows the equivalent Android API functions as wrapper
functions, which can be used in their original forms without any further conversion on the
iOS platform. Table 1 shows a list of the supported Android API functions.
Table 1. Supported APIs Mapping Table between Android and iOS
class
AndroidAPIs
iOSAPIs
System(3)
GetDate, GetTime, getRuntime
GetDate, GetTime, Exit
Handset
Control(13)
seekTo, start, pause, setVolume, vibrate, cancel,
SetBackLight, GetUserNV, PutUserNV, Alive,
LastTime, Slice, Repeat
String(13)
length, StrCpy, delete, append, substring, charAt,
insert, parseInt, PutByte, GetByte, toCharArray,
toString, format
Graphic(24)
setAlpha, SetClip, ResetClip, SetActiveBuffer,
setColorFilter,
SetColor,
setTextSize,
SetFontColor,
SetFontAlign,
SetFontType,
SetPalette, eraseColor, postRotate, setPixel,
createBitmap, drawBitmap, setStyle, getWidth,
getHeight, drawLine, drawRect, drawText,
drawRoundRect, postInvalidate
Mathermatics(8)
abs, nextInt, sin, cos, toRadians, ArrayToVar,
ArrayToArray, HitCheck
PlaySound, StopSound, SetVolume, StartVib,
StopVib, SetTimer, SetTimer1, SetTimer2,
ResetTimer, ResetTimer1, ResetTimer2
StrLen, StrCpy, StrSub, StrCat, GetChar,
GetCharString, PutChar, AsciiToInt, PutByte,
GetByte, PutBytes, GetBytes, MakeStr1,
MakeStr2, MakeStr3
SetAlpha, SetClip, ResetClip, SetActiveBuffer,
SetGamma, SetColor, SetFont, SetFontColor,
SetFontAlign,
SetFontType,
SetPalette,
SetImageAlpha, Clear, ClearRGB, ClearWhite,
ClearBlack,
PutPixel,
CopyImage,
CopyImageDir,CopyImagePal,
CopyImageDirPal,
CopyImageEx,
CopyImageTile,
DrawLine,
DrawHLine,
DrawRect, DrawStr, DrawText, DrawStrSolid,
DrawStrSolid2,
FillRect,
FillRectEx,
FillEllipse,
SaveLCD,
RestoreLCD,
CopyLCD, Flush
Abs, Rand, RandRatio, Sin100, Cos100,
ArrayToVar, ArrayToArray, HitCheck
3.4. Source Translator
The source translator receives the Android source codes that are output by the contents
analyzer and translates them into iOS source codes which are semantically equivalent and
execute the execute the same actions as the Android contents. Source translators have been
created so that they can overcome the differences of the platforms and automatically translate
the game source programs using compiler writing technology. Compiler technology analyzes
programming grammar and syntax and provides a method for automatic translation into
another language [7-9, 11-12, 14]. Figure 12 is a depiction of the source translator model.
Source translators can be largely divided into the source analysis module and source
translation module. The source analysis modules receive Android source code inputs and
carries out lexical and syntax analysis to create an Abstract Syntax Tree (AST). The lexical
analyzer analyzes the source codes and delivers the results to the syntax analyzer.The syntax
analyzer uses the token information obtained from the lexical analyzer and the parsing table
created by the Parser Generating System (PGS) to analyze the syntax of the program. The
results of the syntax analyze output error messages about wrong programs, and for correct
syntax, results are created in the form of a syntax tree. This tree is the Abstract Syntax Tree
(AST) which is used in the source translation module.
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Figure 12. Source Translator Model
The source translation module traverses the AST and generates iOS source codes which
are semantically equivalent to the Android source codes.The source translation module which
receives AST as an inputbegins a successive search from the tree's most significant root.
During the search process, if a significant node appears, the pattern matching source writer
receives the node and translates it into an iOS sentence. When the entire AST search process
is finished, the pattern matching source writer analyzes the nodes until now and creates each
of the translated source codes into one file, this is the iOS source code.
Figure 13 shows the screen of the source translator. The list on the left is the list of
Android files to be translated and the list on the right is a list of the converted iOS files.
When the conversion button is pressed, the source translator automatically converts the
sources.
Figure 13. Screen of the Source Translator
Figure 14 shows an example of searching the AST of anAndroid program created by the
syntax analyzer and converting it into an iOS program.\
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AST
Android program
:
Nonterminal: PROGRAM
Nonterminal: CLASS_DCL
Terminal: SuperClass
Nonterminal: CLASS_BODY
Nonterminal: FIELD_DCL
Nonterminal: DCL_SPEC
Nonterminal: INT_TYPE
Nonterminal: VAR_ITEM
Nonterminal: SIMPLE_VAR
Terminal: a
Terminal: 1
Nonterminal: FIELD_DCL
Nonterminal: DCL_SPEC
Nonterminal: INT_TYPE
Nonterminal: VAR_ITEM
Nonterminal: SIMPLE_VAR
Terminal: b
Terminal: 1
Nonterminal: CLASS_DCL
Terminal: SubClass
Nonterminal: EXTENDS
Nonterminal: CLASS_INTERFACE_TYPE
Nonterminal: SIMPLE_NAME
Terminal: SuperClass
Nonterminal: CLASS_BODY
Nonterminal: FIELD_DCL
Nonterminal: DCL_SPEC
Nonterminal: INT_TYPE
Nonterminal: VAR_ITEM
Nonterminal: SIMPLE_VAR
Terminal: a
Terminal: 2
Nonterminal: FIELD_DCL
Nonterminal: DCL_SPEC
Nonterminal: DOUBLE_TYPE
Nonterminal: VAR_ITEM
Nonterminal: SIMPLE_VAR
Terminal: b
Terminal: 2.0
Nonterminal: METHOD_DCL
Nonterminal: METHOD_HEAD
Nonterminal: METHOD_ITEM
Terminal: output
Nonterminal: METHOD_BODY
Nonterminal: BLOCK (start : 9 end : 12)
Nonterminal: EXPRESSION_ST
Nonterminal: METHOD_CALL
Nonterminal:QUALIFIED_NAME
Nonterminal:QUALIFIED_NAME
Nonterminal:SIMPLE_NAME
Terminal: System
Terminal: out
Terminal: printf
Nonterminal: ARGUMENT_LIST
Terminal: "base : a = %d,
extend : a = %d"
Nonterminal: SUPER_FIELD
Terminal: a
Nonterminal: SIMPLE_NAME
Terminal: a
:
class SuperClass{
int a = 1;int b = 2;
}
class SubClass extends SuperClass{
int a = 3;double b = 4.0;
void output(){
System.out.printf("base : a = %d, extend : a = %d", super.a, a);
System.out.printf("base : b = %d, extend : b = %d", super.b, b);
}
}
public class exam{
public static void main(String[] args){
SubClassobj = new SubClass();
obj.output();
}
}
iOS program
@interface SuperClass : NSObject{
int a;int b;
}
@property int a, b;-(id)init;@end
@implementation SuperClass
@synthesize a, b;
-(id)init{ a = 1;b = 2;
return self;
}
@end
@interface SubClass : SuperClass{
int _a;double _b;
}
@property int _a;@property double _b;
-(id)init;-(void)output;@end
@implementation SubClass
@synthesize _a, _b;
-(id)init{
self = [super init];
a = 3;_b = 4.0;
return self;
}
-(void)output{
NSLog(@” base : a : %d, extend a: %d”, a, _a);
NSLog(@” base : b : %d, extend b : %d”, b, _b);
}
@end
int main(void){
SubClass *p = [[SubClassalloc]init];
[p output];
}
Figure 14. Example of the AST and a Source Translation
4. Experimental Results
In this paper, the Android-to-OS smart game converter was used to automatically convert
smart game contents from the Android platform to the iOS platform. The results of the
conversion were then compared. The emulators that were used to execute game contents are
the Android 4.0.3 emulator and the iOS 7.1 emulator.
Table 2. Platform and Emulator
Copyright ⓒ 2014 SERSC
Platform
Emulator
Method
Android
Android4.0.3 Emulator
Native
iOS
iOS 7.1Emulator
Native
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Figures 15, 16 and 17 shows the execution of the games such as a game A-"Aiolos", a
game B-"Musado" and a game C-"Elemental Forces".
Figure 15. Execution Results of the Game "Aiolos" in Android and iOS
Figure 16. Execution Results of the Game "Musado" in Android and iOS
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Figure 17. Execution Results of the Game "Elemental Force" in Android and
iOS
5. Conclusions and Further Researches
With the recent appearance of smart phones, the mobile game market is experiencing high
growth rates each year, and game content has become killer content in the mobile market.
However, differences in smart platforms have required repeated development or conversion
of mobile game content for use on multiple platforms.
The automatic smart game converter Android-to-iOS presented in this paper offers a
means to solve the problems of different smart platforms. It can ensure quick and automatic
conversion of existing Androidsmart game content into iOSgame content, thus increasing the
reusability of existing content. In addition, the time and expense required throughout the
development and conversion processes in order to provide game content designed for the
Android platform on the iOSplatform can be significantly reduced. In the future, research on
increasing the running speed of games and experiments in actual devices' environments are
expected to create optimized graphics, source code translations, and APIs for each platform
and device.
Acknowledgements
This Research was supported by Seokyeong University in 2012.
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Authors
JaeHyun Kim, he received the B.S. degree from the Dept. of
Mathematics, Hanyang University, Seoul, Korea, in 1986, and M.S. and
Ph.D. degrees from Dept. of Statistics, Dongguk University, and Seoul,
Korea in 1989 and 1996, respectively. He was a chairman of Dept. of
Internet Information 2002-2007. Currently, he is a member of the Korean
Data & Information Science Society and a Professor of Dept. of
Computer Engineering, Seokyeong University, Seoul, Korea. His
research areas include mobile programming, cloud system and data
analysis.
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Vol.8, No.9 (2014)
YangSun Lee, he received the B.S. degree from the Dept. of
Computer Science, Dongguk University, Seoul, Korea, in 1985, and
M.S. and Ph.D. degrees from Dept. of Computer Engineering,
Dongguk University, and Seoul, Korea in 1987 and 2003,
respectively. He was a Manager of the Computer Center, Seokyeong
University from 1996-2000, a Director of Korea Multimedia Society
from 2004-2014, a General Director of Korea Multimedia Society
from 2005-2006, 2009. Also, he was a Director of Korea
Information Processing Society from 2006-2013 and a President of a
Society for the Study of Game at Korea Information Processing
Society from 2006-2010. And, he was a Director of Smart Developer
Association from 2011-2014. Currently, he is a Professor of Dept. of
Computer Engineering, Seokyeong University, Seoul, Korea. His
research areas include smart mobile system solutions, programming
languages, and embedded systems.
Copyright ⓒ 2014 SERSC
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International Journal of Software Engineering and Its Applications
Vol.8, No.9 (2014)
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Copyright ⓒ 2014 SERSC