Posts Tagged ‘JetpackCompose’
[GoogleIO2025] Adaptive Android development makes your app shine across devices
Keynote Speakers
Alex Vanyo works as a Developer Relations Engineer at Google, concentrating on adaptive applications for the Android platform. His expertise encompasses user interface design and responsive layouts, contributing to tools that facilitate cross-device compatibility.
Emilie Roberts serves as a Developer Relations Engineer at Google, specializing in Android integration with Chrome OS. She advocates for optimized experiences on large-screen devices, drawing from her background in software engineering to guide developers in multi-form factor adaptations.
Abstract
This analysis explores the principles of adaptive development for Android applications, emphasizing strategies to ensure seamless performance across diverse hardware ecosystems including smartphones, tablets, foldables, automotive interfaces, and extended reality setups. It examines emerging platform modifications in Android 16, updates to Jetpack libraries, and innovative tooling in Android Studio, elucidating their conceptual underpinnings, implementation approaches, and potential effects on user retention and developer workflows. By evaluating practical demonstrations and case studies, the discussion reveals how these elements promote versatile, future-proof software engineering in a fragmented device landscape.
Rationale for Adaptive Strategies in Expanding Ecosystems
Alex Vanyo and Emilie Roberts commence by articulating the imperative for adaptive methodologies in Android development, tracing the evolution from monolithic computing to ubiquitous mobile paradigms. They posit that contemporary applications must transcend single-form-factor constraints to embrace an array of interfaces, from wrist-worn gadgets to vehicular displays and immersive headsets. This perspective is rooted in the observation that users anticipate fluid functionality across all touchpoints, transforming software from mere utilities into integral components of daily interactions.
Contextually, this arises from Android’s proliferation beyond traditional handhelds. Roberts highlights the integration of adaptive apps into automotive environments via Android Automotive OS and Android Auto, where permitted categories can now operate in parked modes without necessitating bespoke versions. This leverages existing mobile codebases, extending reach to in-vehicle screens that serve as de facto tablets.
Furthermore, Android 16 introduces desktop windowing enhancements, enabling phones, foldables, and tablets to morph into free-form computing spaces upon connection to external monitors. With over 500 million active large-screen units, this shift democratizes desktop-like productivity, allowing arbitrary resizing and multitasking. Vanyo notes the foundational AOSP support for connected displays, poised for developer previews, which underscores a methodological pivot toward hardware-agnostic design.
The advent of Android XR further diversifies the landscape, positioning headsets as spatial computing hubs where apps inhabit immersive realms. Home space mode permits 2D window placement in three dimensions, akin to boundless desktops, while full space grants exclusive environmental control for volumetric content. Roberts emphasizes that Play Store-distributed mobile apps inherently support XR, with adaptive investments yielding immediate benefits in this nascent arena.
Implications manifest in heightened user engagement; multi-device owners exhibit tripled usage in streaming services compared to single-device counterparts. Methodologically, this encourages a unified codebase strategy, averting fragmentation while maximizing monetization. However, it demands foresight in engineering to accommodate unforeseen hardware, fostering resilience against ecosystem volatility.
Core Principles and Mindset of Adaptive Design
Delving into the ethos, Vanyo defines adaptivity as a comprehensive tactic that anticipates the Android spectrum’s variability, encompassing screen dimensions, input modalities, and novel inventions. This mindset advocates for a singular application adaptable to phones, tablets, foldables, Chromebooks, connected displays, XR, and automotive contexts, eschewing siloed variants.
Roberts illustrates via personal anecdote: transitioning from phone-based music practice to tablet or monitor-enhanced sessions necessitates consistent features like progress tracking and interface familiarity. Disparities risk user attrition, as alternatives offering cross-device coherence gain preference. This user-centric lens complements business incentives, where adaptive implementations correlate with doubled retention rates, as evidenced by games like Asphalt Legends Unite.
Practically, demonstrations of the Socialite app—available on GitHub—exemplify this through a list-detail paradigm via Compose Adaptive. Running identical code across six devices, it dynamically adjusts: XR home space resizes panes fluidly, automotive interfaces optimize for parked interactions, and desktop modes support free-form windows. Such versatility stems from libraries detecting postures like tabletop on foldables, enabling tailored views without codebase bifurcation.
Analytically, this approach mitigates development overhead by centralizing logic, yet requires vigilant testing against configuration shifts to preserve state and avoid visual artifacts. Implications extend to inclusivity, accommodating diverse user scenarios while positioning developers to capitalize on emerging markets like XR, projected to burgeon.
Innovations in Tooling and Libraries for Responsiveness
Roberts and Vanyo spotlight Compose Adaptive 1.1, a Jetpack library facilitating responsive UIs via canonical patterns. It categorizes windows into compact, medium, and expanded classes, guiding layout decisions—e.g., bottom navigation for narrow views versus side rails for wider ones. The library’s supporting pane abstraction manages list-detail flows, automatically transitioning based on space availability.
Code exemplar:
val supportingPaneScaffoldState = rememberSupportingPaneScaffoldState(
initialValue = SupportingPaneScaffoldValue.Hidden
)
SupportingPaneScaffold(
state = supportingPaneScaffoldState,
mainPane = { ListContent() },
supportingPane = { DetailContent() }
)
This snippet illustrates dynamic pane revelation, adapting to resizes without explicit orientation handling. Navigation 3 complements this, decoupling navigation graphs from UI elements for reusable, posture-aware routing.
Android Studio’s enhancements, like the adaptive UI template wizard, streamline initiation by generating responsive scaffolds. Visual linting detects truncation or overflow in varying configurations, while emulators simulate XR and automotive scenarios for holistic validation.
Methodologically, these tools embed adaptivity into workflows, leveraging Compose’s declarative paradigm for runtime adjustments. Contextually, they address historical assumptions about fixed orientations, preparing for Android 16’s disregard of such restrictions on large displays. Implications include reduced iteration cycles and elevated quality, though necessitate upskilling in reactive design principles.
Platform Shifts and Preparation for Android 16
A pivotal revelation concerns Android 16’s cessation of honoring orientation, resizability, and aspect ratio constraints on displays exceeding 600dp. Targeting SDK 36, activities must accommodate arbitrary shapes, ignoring portrait/landscape mandates to align with user preferences. This standardization echoes OEM overrides, enforcing free-form adaptability.
Common pitfalls include clipped elements, distorted previews, or state loss during rotations—issues users encounter via overrides today. Vanyo advises comprehensive testing, layout revisions, and state preservation. Transitional aids encompass opt-out flags until SDK 37, user toggles, and game exemptions via manifest or Play categories.
For games, Unity 6 integrates configuration APIs, enabling seamless handling of size and density alterations. Samples guide optimizations, while titles like Dungeon Hunter 5 demonstrate foldable integrations yielding retention boosts.
Case studies reinforce: Luminar Neo’s Compose-built editor excels offline via Tensor SDK; Cubasis 3 offers robust audio workstations on Chromebooks; Algoriddim’s djay explores XR scratching. These exemplify methodological fusion of libraries and testing, implying market advantages through device ubiquity.
Strategic Implications and Forward Outlook
Adaptivity emerges as a strategic imperative amid Android’s diversification, where single codebases span ecosystems, enhancing loyalty and revenue. Platform evolutions like desktop windowing and XR demand foresight, with tools mitigating complexities.
Future trajectories involve deeper integrations, potentially with AI-driven layouts, ensuring longevity. Developers are urged to iterate compatibly, avoiding presumptions to future-proof against innovations, ultimately enriching user experiences across the Android continuum.
Links:
[GoogleIO2024] What’s New in Android: Innovations in AI, Form Factors, and Productivity
Android’s progression integrates cutting-edge AI with versatile hardware support, as detailed by Jingyu Shi, Rebecca Gutteridge, and Ben Trengrove. Their overview encompassed generative capabilities, adaptive designs, and enhanced tools, reflecting a commitment to seamless user and developer experiences.
Integrating Generative AI for On-Device and Cloud Features
Jingyu introduced Gemini models optimized for varied tasks: Nano for efficient on-device processing via AI Core, Pro for broad scalability, and Ultra for intricate scenarios. Accessible through SDKs like AI Edge, these enable privacy-focused applications, such as Adobe’s document summarization or Grammarly’s suggestions.
Examples from Google’s suite include Messages’ stylistic rewrites and Recorder’s transcript summaries, all network-independent. For complex needs, Vertex AI for Firebase bridges prototyping in AI Studio to app integration, supported by comprehensive guides on prompting and use cases.
Adapting to Diverse Devices and Form Factors
Rebecca addressed building for phones, tablets, foldables, and beyond using Jetpack Compose’s declarative approach. New adaptive libraries, like NavigationScaffold, automatically adjust based on window sizes, simplifying multi-pane layouts.
Features such as pane expansion in Android 15 allow user-resizable interfaces, while edge-to-edge defaults enhance immersion. Predictive back animations respond intuitively to gestures, and stylus handwriting converts inputs across fields, boosting productivity on large screens.
Enhancing Performance, Security, and Developer Efficiency
Ben highlighted Compose’s optimizations, including strong skipping mode for reduced recompositions and faster initial draws. Kotlin Multiplatform shares logic across platforms, with Jetpack libraries like Room in alpha.
Security advancements feature Credential Manager’s passkey support and Health Connect’s expanded APIs. Performance tools, from Baseline Profiles to Macrobenchmark, streamline optimizations. Android Studio’s Gemini integration aids coding, debugging, and UI previews, accelerating workflows.
These elements collectively empower creators to deliver responsive, secure applications across ecosystems.
Links:
[KotlinConf2023] Transforming Farmers’ Lives in Kenya: Apollo Agriculture’s Android Apps with Harun Wangereka
Harun Wangereka, a Software Engineer at Apollo Agriculture and a Google Developer Expert for Android, delivered an inspiring presentation at KotlinConf’23 about how his company is leveraging Android technology to change the lives of farmers in Kenya. His talk detailed Apollo Agriculture’s two core Android applications, built entirely in Kotlin, which are offline-first and utilize server-driven UI (SDUI) with Jetpack Compose to cater to the unique challenges of their user base. Harun is also active in Droidcon Kenya.
Apollo Agriculture’s mission is to empower small-scale farmers by bundling financing, high-quality farm inputs, agronomic advice, insurance, and market access. Their tech-based approach uses satellite data and machine learning for credit decisions and automated operations to maintain low costs and scalability. The customer journey involves signup via agents or SMS/USSD, kyc data collection (including GPS farm outlines), automated credit decisions (often within minutes), input pickup from agro-dealers, digital advice via voice trainings, and loan repayment post-harvest.
Addressing Unique Challenges in the Kenyan Context
Harun highlighted several critical challenges that shaped their app development strategy:
* Low-Memory Devices: Many agents and farmers use entry-level Android devices with limited RAM and storage. The apps need to be lightweight and performant.
* Low/Intermittent Internet Bandwidth: Internet connectivity can be unreliable and expensive. An offline-first approach is crucial, allowing agents to perform tasks without constant internet access and sync data later.
* Diverse User Needs and Rapid Iteration: The agricultural domain requires frequent updates to forms, workflows, and information provided to farmers and agents. A flexible UI system that can be updated without frequent app releases is essential.
These challenges led Apollo Agriculture to adopt a server-driven UI (SDUI) approach. Initially implemented with Anko (a deprecated Kotlin library for Android UI), they later rewrote this system entirely using Jetpack Compose.
Server-Driven UI with Jetpack Compose
The core of their SDUI system relies on JSON responses from the server that define the UI components, their properties, validations, and conditional logic.
Key aspects of their implementation include:
* Task-Based Structure: The app presents tasks to agents (e.g., onboarding a farmer, collecting survey data). Each task is represented by a JSON schema from the server.
* Dynamic Form Rendering: The JSON schema defines various UI elements like text inputs, number inputs, date pickers, location pickers (with map integration for capturing farm boundaries), image inputs (with compression), and more. These are dynamically rendered using Jetpack Compose.
* Stateful Composable Components: Harun detailed their approach to building stateful UI components in Compose. Each question or input field manages its own state (value, errors, visibility) using remember and mutableStateOf. Validation logic (e.g., required fields, min/max length) is also defined in the JSON and applied dynamically.
* Triggers and Conditionals: The JSON schema supports triggers (e.g., “on save”) and complex conditional logic using an internal tool called “Choice Expressions” and an implementation of JSON Schema. This allows UI elements or entire sections to be shown/hidden or enabled/disabled based on user input or other conditions, enabling dynamic and context-aware forms.
* Offline First: Task schemas and user data are stored locally, allowing full offline functionality. Data is synced with the server when connectivity is available.
* Testing: They extensively test their dynamic UI components and state logic in isolation, verifying state changes, validation behavior, and conditional rendering.
Harun shared examples of the JSON structure for defining UI elements, properties (like labels, hints, input types), validators, and conditional expressions. He walked through how a simple text input composable would manage its state, handle user input, and apply validation rules based on the server-provided schema.
Learnings and Future Considerations
The journey involved migrating from Anko to Jetpack Compose for their SDUI renderer, which Compose’s reactive DSL made more manageable and maintainable. They found Compose to be well-suited for building dynamic, stateful UIs.
Challenges encountered included handling keyboard interactions smoothly with scrolling content and managing the complexity of deeply nested conditional UIs.
When asked about open-sourcing their powerful form-rendering engine, Harun mentioned it’s a possibility they are considering, as the core logic is already modularized, and community input could be valuable. He also noted that while some pricing information is dynamic (e.g., based on farm size), they try to standardize core package prices to avoid confusion for farmers.
Harun Wangereka’s talk provided a compelling case study of how Kotlin and Jetpack Compose can be used to build sophisticated, resilient, and impactful Android applications that address real-world challenges in demanding environments.