Commit 7ab9fd1

HarmonyOS NEXT is a distributed operating system developed to

support HarmonyOS native apps. To support the new and independent Harmony ecosystem, developers are required to migrate their

applications from Android to HarmonyOS. However, HarmonyOS

utilizes ArkTS, a superset of TypeScript, as the programming language for application development. Hence, migrating applications

to HarmonyOS requires translating programs across different program languages, e.g., Java, which is known to be very challenging,

especially for concurrency programs. Java utilizes shared memory to implement concurrency programs, while ArkTS relies on

message passing (i.e., Actor model). This paper presents an LLMbased concurrent Java program to ArkTS converter. This converter

leverages the sophisticated code comprehension and generation

capabilities of large language models (LLMs) to streamline the translation process. By integrating the SharedArrayBuffer API native to

ArkTS, we’ve crafted ThreadBridge, a shared library that replicates

Java’s shared memory paradigm. Employing this library and LLM’s

Chain-of-thought mechanism, our approach divides the translation

challenge into specialized chains: the TypeScript (TS) chain, the

concurrency chain, and the synchronization chain. These targeted

chains are designed to efficiently translate Java’s source code into

its ArkTS equivalent, handling TypeScript-specific syntax, concurrency patterns, and synchronization logic with precision. In particular, this study provides a set of effective solutions to overcome the

differences in concurrency models between Java and ArkTS. With

this converter, developers can reduce manual code rewriting and

accelerate application adaptation and deployment on HarmonyOS

NEXT. Experimental results show that our converter successfully

compiles 66% of the 53 test samples, with an accuracy rate of 69%

for the successfully compiled results. In conclusion, our approach

demonstrates promising potential in handling the conversion of

concurrent Java programs to ArkTS, providing a foundation for

further improvement and optimization.

First you need to install LangChain and its package of openai

Set environment variables `OPENAI_API_KEY` to your api_key of openai.

To run the AST, you need to install Java 17.

To perform compilation check, you need to install tsc.

Install `streamlit` library.

Go to LangChain directory，Enter on the command line.