|Original author(s)||Dan Bornstein|
|Operating system||Linux kernel|
|License||Apache License 2.0|
Dalvik is the process virtual machine (VM) in Google's Android operating system, which, specifically, executes applications written for Android. This makes Dalvik an integral part of the Android software stack, which is typically used on mobile devices such as mobile phones and tablet computers, as well as more recently on devices such as smart TVs and wearables.
Programs are commonly written in Java and compiled to bytecode for the Java virtual machine, which is then translated to Dalvik bytecode and stored in .dex (Dalvik EXecutable) and .odex (Optimized Dalvik EXecutable) files; related terms odex and de-odex are associated with respective bytecode conversions. The compact Dalvik Executable format is designed for systems that are constrained in terms of memory and processor speed.
Unlike Java VMs, which are stack machines, the Dalvik VM uses a register-based architecture that requires fewer, typically more complex virtual machine instructions. Dalvik programs are written in Java using the Android application programming interface (API), compiled to Java bytecode, and converted to Dalvik instructions as necessary.
A tool called dx is used to convert Java .class files into the .dex format. Multiple classes are included in a single .dex file. Duplicate strings and other constants used in multiple class files are included only once in the .dex output to conserve space. Java bytecode is also converted into an alternative instruction set used by the Dalvik VM. An uncompressed .dex file is typically a few percent smaller in size than a compressed Java archive (JAR) derived from the same .class files.
The Dalvik executables may be modified again when installed onto a mobile device. In order to gain further optimizations, byte order may be swapped in certain data, simple data structures and function libraries may be linked inline, and empty class objects may be short-circuited, for example.
Being optimized for low memory requirements, Dalvik has some specific characteristics that differentiate it from other standard VMs:
- The VM was slimmed down to use less space.
- The constant pool has been modified to use only 32-bit indices to simplify the interpreter.
- Standard Java bytecode executes 8-bit stack instructions. Local variables must be copied to or from the operand stack by separate instructions. Dalvik instead uses its own 16-bit instruction set that works directly on local variables. The local variable is commonly picked by a 4-bit 'virtual register' field. This lowers Dalvik's instruction count and raises its interpreter speed.
According to Google, the design of Dalvik permits a device to run multiple instances of the VM efficiently.
Generally, stack-based machines must use instructions to load data on the stack and manipulate that data, and, thus, require more instructions than register machines to implement the same high level code, but the instructions in a register machine must encode the source and destination registers and, therefore, tend to be larger. This difference is primarily of importance to VM interpreters for which opcode dispatch tends to be expensive along with other factors similarly relevant to just-in-time compilation.
However, tests performed on ARM devices by Oracle (owner of the Java technology) in 2010 with standard non-graphical Java benchmarks on Java SE embedded seemed to show it to be faster, by 2 to 3 times, than Android 2.2 (the initial release to include a just-in-time compiler) that they compared to (both based on Java SE 6).[dated info]
Furthermore, benchmarks performed on Android device still show (as of March 2014) up to a factor 100 between native applications and a Dalvik application on the same Android device.[original research?][improper synthesis?] Upon running benchmarks using the early interpreter of 2009, both JNI and native code showed an order of magnitude speed up.
Licensing and patents
Dalvik is published under the terms of the Apache License 2.0. Google says that Dalvik is a clean-room implementation rather than a development on top of a standard Java runtime, which would mean it does not inherit copyright-based license restrictions from either the standard-edition or open-source-edition Java runtimes. Oracle and some reviewers dispute this.
On August 12, 2010, Oracle, which acquired Sun Microsystems in April 2009 and therefore owns the rights to Java, sued Google over claimed infringement of copyrights and patents. Oracle alleged that Google, in developing Android, knowingly, directly and repeatedly infringed Oracle's Java-related intellectual property. In May 2012, the jury in this case found that Google did not infringe on Oracle's patents, and the trial judge ruled that the structure of the Java APIs used by Google was not copyrightable. The parties agreed to zero dollars in statutory damages for 9 lines of copied code.
On May 9, 2014, the Federal Circuit partially reversed the district court ruling, ruling in Oracle's favor on the copyrightability issue, and remanding the issue of fair use back to the district court.
- Android software development
- Application virtualization
- Comparison of application virtual machines
- Comparison of Java and Android API
- JEB Decompiler Dalvik (DEX and APK) Decompiler
- Dalvik Turbo virtual machine, a proprietary alternative Dalvik implementation
- Journal entry referencing the source of the name
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The results show that although Androids new JIT is an improvement over its interpreter only implementation, Android is still lagging behind the performance of our Hotspot enabled Java SE Embedded. As you can see from the above results, Java SE Embedded can execute Java bytecodes from 2 to 3 times faster than Android 2.2.
- Hyeong-Seok Oh, Beom-Jun Kim, Hyung-Kyu Choi, Soo-Mook Moon (2012). "Evaluation of Android Dalvik virtual machine". Association for Computing Machinery. Retrieved 2014-03-23.
In the JITC mode, however, Dakvik is slower than HotSpot by more than 2.9 times and its generated code size is not smaller than HotSpot's due to its worse code quality and trace-chaining code.
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The results show that native C applications can be up to 30 times as fast as an identical algorithm running in Dalvik VM. Java applications can become a speed-up of up to 10 times if utilizing JNI.
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The definition of a “clean room” implementation is that the engineers writing the code have no direct exposure to the original, copyrighted material, including code, specifications, and other documentation. That’s a problem for Google, as I noted in yesterday’s post, because there is substantial evidence that the engineers working on the project had direct access to the copyrighted material.
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A major portion of the Oracle’s claims are based on 9 lines of code contained within Java.Util.Arrays.rangeCheck(). Here is the code in question:...
- Rosenblatt, Seth (May 9, 2014). "Court sides with Oracle over Android in Java patent appeal". CNET. Retrieved 2014-05-10.
- "ORACLE AMERICA, INC. , Plaintiff - Appellant, v. GOOGLE INC., Defendant - Cross - Appellant.". Court of Appeals for the Federal Circuit. May 9, 2014. Retrieved 2014-05-10.
- Dalvik Instruction Set – official Android documentation
- Dex Executable Format – official Android documentation
- Pamela Jones (August 16, 2010). "Oracle America's complaint against Google, as text". Groklaw.
- Google I/O 2010 - A JIT Compiler for Android's Dalvik VM on YouTube
- Dalvik VM Internals – presentation from Google I/O 2008, by Dan Bornstein
- Oracle v Google Copyright Claims Decompiled