Why Android Apps Don't Convert Java/Kotlin to ELF: The Power of ART and Dalvik

Introduction

Have you ever wondered why Android apps, built with Java or Kotlin, rely on the Android Runtime (ART) or Dalvik Virtual Machine instead of converting directly to ELF binaries for native execution? At first glance, skipping ELF might seem like sacrificing speed, but this design choice empowers Android to be flexible, portable, and developer-friendly. In this blog, we'll explore why ART and Dalvik are at the heart of Android's architecture and how they strike the perfect balance between performance and usability.

What Are ELF Files and How Do They Work in Android?

ELF (Executable and Linkable Format) is a standard file format used in Linux-based systems for executables, shared libraries, and core dumps. In Android, ELF files are primarily used for native libraries (e.g., .so files) and system binaries. These files provide a structured way to store machine code, making them essential for executing low-level operations and interfacing with the hardware. While your Java/Kotlin code runs on ART/Dalvik, it relies on ELF files for accessing native functionality and system-level features.

Java/Kotlin Code in Android Apps

1. Compilation Process:

   • Java/Kotlin code is first compiled into bytecode (as .class files).

   • The Android build system (e.g., Gradle) uses the D8/R8 compiler to convert these .class files into DEX (Dalvik Executable) files. These .dex files are packaged into the APK (or AAB).

2. Execution Environment:

   • When you install the app on your Android device:

     • The Android Runtime (ART) or the older Dalvik Virtual Machine (DVM) takes the .dex files and interprets or compiles them into machine code that can run on the device's CPU.

     • ART typically performs Ahead-of-Time (AOT) or Just-in-Time (JIT) compilation to translate DEX bytecode into machine code.

Benefits of Using ART/Dalvik

ART/Dalvik provides a managed runtime environment that brings several advantages:

1. Cross-Platform Compatibility

• Java/Kotlin Bytecode Independence: Bytecode (DEX format) is platform-independent, meaning it can run on any architecture (e.g., ARM, x86) without recompilation.

• Portability: With ART/Dalvik, the app doesn’t need to be recompiled into architecture-specific ELF binaries. Instead, the runtime handles this, making it easier to support multiple device architectures.

2. Dynamic Features

• Reflection and Dynamic Loading: Features like reflection, dynamic class loading, and runtime code execution (e.g., Class.forName()) are easier to implement in a virtual machine.

• Hot Code Patching: The runtime enables dynamic updates to apps without requiring ELF recompilation or app restarts.

3. Efficient Memory Management

• Garbage Collection (GC): ART/Dalvik provides automatic memory management via garbage collection, reducing the risk of memory leaks and ensuring efficient memory usage.

• If the app were converted into an ELF binary, managing memory would need to be done manually, increasing complexity and the likelihood of bugs.

4. Optimized Execution

• JIT (Just-In-Time) Compilation:

  • During execution, ART/Dalvik can optimize code based on runtime conditions (e.g., frequently used methods are compiled and optimized dynamically).

• AOT (Ahead-Of-Time) Compilation:

  • ART allows pre-compilation of bytecode into machine code (stored in .oat files) to improve startup time and execution speed.

5. Development Speed

• Ease of Debugging: The managed runtime provides better debugging, profiling, and exception-handling mechanisms.

• Rapid Iteration: Developers can write code once, and ART/Dalvik handles compilation and optimization at runtime, without needing separate ELF binaries for each platform.

Why Not Convert Bytecode to ELF?

While converting Java/Kotlin bytecode to ELF binaries may potentially increase raw execution speed, it introduces significant trade-offs:

1. Loss of Platform Independence

• If bytecode were converted to ELF, developers would need to build separate ELF binaries for each supported architecture (e.g., ARM, x86, ARM64). This process would increase complexity and make apps harder to distribute and maintain.

2. Reduced Flexibility

• ELF binaries are static and lack the dynamic capabilities of bytecode. This would limit features like dynamic class loading, runtime code injection, and the use of reflection.

3. Increased Development Overhead

• Without a managed runtime, developers would need to handle memory management, threading, and other low-level tasks manually, increasing the risk of bugs and making development slower.

4. Increased Storage Requirements

• ELF binaries for multiple architectures would increase APK size, especially for apps that need to support a wide range of devices.

5. Runtime Optimization Benefits

• ART can optimize code at runtime based on actual usage patterns, something static ELF binaries cannot do. For example, ART can inline frequently called methods or eliminate unused code during execution.

When Does ART/Dalvik Compile to Machine Code?

ART/Dalvik does compile the bytecode into machine code for performance reasons, but it doesn’t produce ELF files. Instead, it uses:

• Ahead-of-Time (AOT) Compilation:

  • At install time, ART compiles bytecode into machine code stored in .oat or .odex files.

  • These are architecture-specific but not full ELF binaries, as they rely on the runtime for execution.

• Just-In-Time (JIT) Compilation:

  • During app execution, ART dynamically compiles parts of the bytecode to machine code based on runtime needs.

Performance vs. Flexibility: The Android Balancing Act

• Direct ELF Conversion: Would make the app slightly faster (because there’s no runtime interpretation or JIT overhead), but it sacrifices flexibility and portability.

• ART/Dalvik Approach: Trades off a bit of raw speed for huge gains in compatibility, dynamic features, and ease of development.

Conclusion

Using ART/Dalvik instead of directly converting bytecode to ELF is a design choice aimed at balancing performance with developer productivity, app portability, and runtime flexibility. While ELF binaries might offer faster execution in specific cases, the trade-offs in terms of compatibility, memory management, and dynamic features make ART/Dalvik the better choice for the diverse Android ecosystem.