pith. sign in

arxiv: 2409.16656 · v2 · pith:JGQFACKKnew · submitted 2024-09-25 · 💻 cs.SE

GUIMigrator: Semantics-Preserving Transpilation from Android XML to Compose and SwiftUI

classification 💻 cs.SE
keywords guimigratorandroidcomposeswiftuicross-platformdeclarativejetpackmanual
0
0 comments X
read the original abstract

Constructing user interfaces (UIs) is one of the most resource-intensive tasks in mobile development, often consuming more than half of overall effort. Although declarative frameworks such as Jetpack Compose (Android) and SwiftUI (iOS) have become mainstream, the majority of existing Android apps still rely on legacy XML-based layouts. Migrating these UIs to declarative paradigms is essential for maintainability and cross-platform reuse, but manual migration is costly, error-prone, and difficult to scale. We present GUIMigrator, a semantics-preserving framework that automates the migration of Android XML-based UIs to Jetpack Compose and SwiftUI. We design the Semantic UI Transpiler (SUT), which abstracts layout structures and resource semantics from legacy XML and systematically re-expresses them using the component abstractions and idioms of modern declarative frameworks. This design ensures that migrated UIs preserve both visual fidelity and functional equivalence, while generating idiomatic, compilable code that maintains cross-platform consistency with minimal manual intervention. By separating semantic interpretation from platform-specific realization, GUIMigrator provides a deterministic yet extensible basis for cross-platform modernization, avoiding the unpredictability of purely generative approaches. We evaluate GUIMigrator on 31 open-source applications across ten domains. Results show that GUIMigrator achieves high migration completeness and strong visual similarity (81.9% SSIM on Jetpack Compose and 78.2% on SwiftUI on average), while maintaining substantially higher project-wide semantic coherence (PSC) than modern LLM baselines. In addition, GUIMigrator reduces manual development effort by over 90%.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Porting Declarative UI to HarmonyOS: A Heuristic-guided LLM Approach

    cs.SE 2026-06 unverdicted novelty 6.0

    ArkTrans achieves up to 90.67% compilable ArkUI translations from KJC/SwiftUI using heuristic LLM guidance and empirical post-fixing rules, versus 0% for direct or one-shot prompting on a 100-sample benchmark.