Large apps lose users before they even open. A big download takes longer on a slow network. It also consumes storage that users may not want to spare. Dynamic feature bundles solve this problem by splitting heavy features from the base app. The base app stays small and heavy features download only when a user needs them. This guide explains how to design that split.
Start by measuring your app size by feature. List each feature and its code and resource size. A video editor feature may add many megabytes. A simple settings feature adds very little. Split only features that are large and used by a subset of users. A small feature that everyone uses should stay in the base app.
Design the base app to work fully without any dynamic feature. A user who never downloads a feature should still enjoy the core app. A feature module should add value when installed and it should not break the base app when removed. This independence makes dynamic delivery safe and testable.
Split Features By Use And Size
Split a feature when it is large and optional. A premium filter pack is a good candidate because only some users want it. A core login flow is a poor candidate because every user needs it. A large game level pack is a good candidate because users download levels as they progress. A small help screen is a poor candidate because the split adds complexity without size gain.
Measure the size gain for each candidate split. A split that saves only a few kilobytes is not worth the complexity. A split that saves several megabytes is worth the work. Record the base size before and after each split. A size record helps you prioritise the next split and it proves the benefit to the team.
- Measure size by feature before splitting
- Split large optional features only
- Keep core features in the base app
- Record base size before and after each split
- Test the base app without any module installed
Design On Demand Download Flows
An on demand flow starts when the user taps a feature that is not installed. Show a clear download progress screen with size and time estimates. Allow the user to cancel the download without breaking the base app. Resume a cancelled download later without restarting from zero when the platform supports it. A clear flow reduces frustration during a large download.
Handle download failures gracefully. A network failure should show a retry option and a clear message. A storage failure should explain the storage need and offer cleanup help. Test failure flows on a slow network and on a nearly full device. A failure flow that works well keeps users engaged even when a download fails.
Download design also relates to asset work in the material on extracting graphics and audio from APK files. Large assets inside a feature module dominate its size. Audit assets in each module separately. Remove unused assets from a module before you measure its size gain.
Test Modules In Isolation
Test each module as if it were a separate app. Install the base app alone and confirm core features work. Install one module and confirm its feature works. Remove the module and confirm the base app still works. Isolation testing catches dependencies that a module should not have on another module. A module that depends on another optional module needs redesign.
Test module updates separately from base updates. A module update should not require a base app update when the interface stays stable. Keep the interface between base and module stable across versions. A stable interface allows independent updates and it reduces release risk. Document the interface so future changes respect it.
Handle Version Compatibility
Version compatibility matters when base and module versions drift. A new module may need a new base feature. An old base may not support a new module interface. Check compatibility before a module download starts. Show a clear message when a base update is needed. A compatibility check prevents a broken feature after a successful download.
Test compatibility with the oldest supported base version. A module that works only on the newest base will fail for users who delay updates. Decide whether to require a base update or to support older bases. A requirement is simpler but it can block users. Support for older bases is more work but it reaches more users.
Monitor Download And Usage Data
Monitor how often each module downloads and how often users open it after download. A module that downloads rarely may not deserve its split complexity. A module that downloads often but opens rarely may have a confusing entry point. Use data to decide whether to keep a split or to merge a feature back into the base app.
Monitor download failures by network type and device storage. A high failure rate on slow networks may mean the module is too large for its audience. A high failure rate on low storage devices may mean users need a smaller module. Split a large module further when data shows a clear size problem for a user group.
Keep The Base App Fast
A smaller base app should also feel faster. Measure install time and first launch time after each split. A smaller download installs faster on slow networks. A smaller base also loads faster on low-end devices. Record install and launch times beside size data. A complete picture includes speed as well as size.
Test first launch without any module installed. The base app should show its core features immediately. A base app that waits for a module during first launch defeats the purpose of splitting. Keep first launch independent of optional modules. Independence is the core promise of dynamic delivery.
base_app_size = small
feature_module = on_demand
download_trigger = user_tap
fallback = base_app_onlyThe snippet above is an original example written for this guide. It shows generic module settings that you can adapt to your own project. It does not copy code from any outside source.
The snippet lists the basic states for a dynamic feature flow. Use it as a checklist during design. Confirm that the fallback state works when a module is not installed.
Design Module Discovery For Users
Users cannot download a feature that they cannot find. A dynamic feature needs a clear entry point in the app. A settings screen or a feature gallery can show available modules with size and description. A clear entry point helps users decide whether a module is worth downloading. A hidden module will download rarely no matter how good it is. Discovery design is part of dynamic delivery and it deserves the same care as download design.
Show module size before download so users can judge the cost on a slow network or a low storage device. A size label next to the download button sets expectations. A download without a size label can surprise a user with a large transfer. Surprise downloads cause cancellations and negative reviews. Transparency about size builds trust even for large modules.
Show module status clearly after download. A downloaded module should show as installed with an open action. A module that failed to download should show a retry action. A module that is updating should show progress. Clear status prevents users from tapping download twice or from thinking a feature is missing. Status clarity is especially important when a user switches devices and modules need to reinstall.
Test discovery flows with users who have never seen the app. A new user should find the feature gallery without help. A test with a new user reveals labels that are unclear. Fix unclear labels before release. A discovery flow that works for a new user will work for most users. A flow that only the development team understands will fail in the real world.
Measure discovery data alongside download data. A module with high discovery views but low downloads may have a confusing description or a large size. A module with low discovery views may need a better entry point. Use both metrics to improve discovery and description together. Data driven discovery work keeps dynamic features visible and useful.
Discovery data should also track which entry point users tap most. A feature gallery may outperform a settings link for the same module. A settings link may outperform a banner for another module. Compare entry points and promote the best one for each module. Entry point data turns discovery design from guesswork into measurement.
Common Mistakes
A common mistake is splitting a core feature that every user needs. A core split adds download steps without size benefit for most users. Keep core features in the base app. Split only large optional features.
Another mistake is splitting a tiny feature. A tiny split adds complexity and testing work for little gain. Measure size gain before you split. A split should save a meaningful amount of space.
Some developers also create dependencies between optional modules. A module that needs another optional module can fail when the second module is missing. Keep modules independent. A module should work with the base app alone.
Finally do not ignore download failure flows. A failed download without a clear retry path frustrates users. Test failures on slow networks and low storage devices. A graceful failure flow keeps users engaged.
Frequently Asked Questions
Will dynamic features slow down the app?
No a well designed split keeps the base app fast. Heavy features download only when needed. First launch should not wait for any optional module.
What happens if a module download fails?
The base app should continue to work without the module. Show a retry option and a clear message. Allow the user to try again later without data loss.
Should I split every large feature?
No split only large features that a subset of users wants. Keep core features in the base app. Measure size gain and usage data before each split.
Conclusion
Dynamic feature bundles reduce app size by moving large optional features out of the base app. Split by use and size and design clear download flows. Test modules in isolation and monitor usage data. Your concrete next step is to measure your app size by feature today and pick one large optional feature for a split. Design its download flow and test the base app without it. For related work you can study extracting graphics and audio from APK files and debugging memory leaks with Profiler and Android Studio emulator setup as next steps.
